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School of Computer Science

Automated Scheduling, Optimisation and Planning (ASAP) Research Group

Research Report 2007 - 2008

Welcome � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 3

The LANCS Initiative � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 4

Next Generation Decision Support � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 6

Timetabling � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 8

Sports Scheduling� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 9

Cutting, Packing and Space Management � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 10

Scheduling in the Air Transport Industry � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 12

Healthcare Modelling and Optimisation � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 14

Production Scheduling� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 16

Bioinformatics, Systems and Synthetic Biology � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 17

EPSRC IDEAS Factories � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 19

Outreach� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 20

Professional Activities� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 23

Publications � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 27

Grants � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 34

ASAP Personnel � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 38

PhD Students� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 41

Visiting Fellows/Associated Staff � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 43

How to find us � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 43

Contents

2 A S A P

Welcome to our 2007-2008 research report. The purpose of this

report is to highlight our activity and achievements over this

period. These two years have seen some notable achievements

by the group. In particular, we played a key role in the award of a

£13m programme across four universities (Lancaster, Nottingham,

Cardiff and Southampton) under EPSRC’s Science and Innovation

initiative. The consortium received over £5.4m in total from EPSRC

(Nottingham received £2m) and the institutions have contributed

over £7.5m. Nottingham’s contribution is over £2.4m and includes

the commitment of a new chair and two new lectureships.

In addition, our £2.6m EPSRC grant to explore the automation

of the heuristic design process has matured into an exciting and

groundbreaking initiative which is setting the international agenda

in automated methodologies for heuristic design. At the beginning

of 2009, we hold over £8m for our research activity from a wide

variety of funding bodies including EPSRC, BBSRC, Research

Council of Norway, KTP and industry.

Our strategic aim over the next few years is to continue to flexibly

respond to emerging research opportunities in order to build upon

our transformative research agenda and to extend our activity into

other disciplines and application areas. The cornerstone of our long-

term research strategy is to tackle the complexity and uncertainty

of real world problems and to innovatively address the broad

range of demanding scientific challenges which are generated by

industrial, commercial and service sector requirements. Our overall

strategic aim is to address a broad range of scientific challenges

at the interface of Operational Research and Computer Science

to underpin the exploration and development of computational

search methodologies that emerge from studying the complexity

and uncertainty of real world scheduling, optimisation and decision

support problems. Key strategic goals include:

Automating the Heuristic Design Process: The ASAP group has

set the international agenda in exploring the development of

computational methodologies that can automatically build decision

support systems. The aim is to investigate the extent to which

we can replace human decision making by computer algorithms

that are able to operate at the same level as humans. This is an

extremely challenging aim, which the scientific community is only

just beginning to explore. This has the potential to change the way

that decision support systems are built. It also has the potential to

significantly reduce the resource cost that is often associated with

developing bespoke systems.

Closing the gap between industrial/real world practice and

academic decision support research: We aim to explore dynamic

and complex computational modelling and intelligent decision

support techniques within the context of real world problems such as

transport scheduling (particularly in the airline industry), timetabling,

manufacturing technologies, bioinformatics, production scheduling,

protein folding, DNA mapping, healthcare personnel rostering,

radiotherapy planning and others. We aim to establish new decision

support methodologies that push the boundaries of automated

search methods and the complexity that they are able to handle.

Closing the gap between theoretical understanding and complex

decision support system development: ASAP has been extremely

successful in developing effective methodologies for complex

real world problem solving scenarios. However, the scientific

community’s level of theoretical understanding of what heuristics

work well in what situation is extremely low. Moreover, much of

the theoretical work in this area has dealt with models that are too

simple. We aim to develop a deeper theoretical understanding of

complex real world problem solving scenarios. This would facilitate

much more effective design of computational search methods than

is possible today.

Our strategic goals are undertaken within the context of a broad

inter-disciplinary agenda. Our core research on modelling and

search methodologies has redefined the inter-disciplinary interface

between Operational Research and Computer Science, while our

grounding in diverse applications involves dialogue with many other

disciplines. We aim to underpin an adventurous and ambitious

strategic programme with a clear multi-disciplinary focus that will

draw upon and influence a range of disciplines and new inter-

disciplinary application areas. Indeed, the potential benefits in

providing the grounding for tomorrow’s decision support systems

could be far reaching in laying the foundations for more efficient,

more effective, more environmentally friendly, cheaper, easier-to-

implement and easier-to-use decision support systems across many

industries and sectors.

This report provides a brief overview of the range and breadth of

our work over 2007-2008. We hope that you find it informative,

interesting and useful.

Welcome

3 www�asap�cs�nott�ac�uk

The LANCS Initiative is a collaboration of leading Operational

Research (OR) groups from four UK Universities. Specifically, it was

founded by:

LA Management School, Lancaster University

N School of Computer Science, University of Nottingham

C School of Mathematics, Cardiff University

S School of Mathematics and School of Management,

University of Southampton

Under the EPSRC Science and Innovation program it was awarded

the largest ever grant for OR within the UK – and possibly the largest

ever OR grant in the world. Together with co-funding from the

universities, it is an initiative project with the aim of building

OR theory in order to support OR practice. The Initiative officially

started up in September 2008 and is, therefore, still in the very

early stages, but it is expected to have a significant influence on the

development of OR within the UK, and, indeed, worldwide.

According to EPSRC’s 2004 International Review of OR, the UK

has a strong position in the practical application of OR. However,

in the wider community, there has generally been a ‘gap’ between

the theory and the practice. A primary goal of the LANCS

Initiative is to close this gap, and to contribute towards building

UK capacity in OR by setting the overall long-term national and

international research agenda.

The LANCS initiative is currently organised around six research

themes. Three of these are concerned with application areas that

are vital to the UK: Transport, Healthcare and Green Logistics.

The remaining three are concerned with important theoretical

research directions: Discrete Nonlinear Optimisation, Heuristic

Understanding and Systems to Build Systems, with the last two

being led by Nottingham. These two Nottingham-led themes are

explored in more detail on the opposite page.

The LANCS Initiative

ResearchThemes

GreenLogistics

HeuristicUnderstanding

Systems toBuild Systems

Transport

Healthcare

Discrete andNonlinear

Optimisation

4 A S A P

Many large problems are effectively and efficiently solved by the use of heuristics and meta-heuristics.

Such methods have no guarantee to return optimal solutions, but they often represent appropriate practical

methods to solve real world, large-scale problems. Typically, the methods have been built upon years of

experience. However, there is generally a lack of a deep understanding as to why and when they work. This

lack of understanding means that significant time-consuming trial and error experimentation is often required.

The aim of this research cluster is to strengthen the theoretical understanding of how heuristics work.

A particular aspect of this thematic programme is to better understand the landscapes of real search

spaces. The aim is to reduce the need for trial and error by developing our understanding so that

expensive mistakes (in terms of both time and resources) can be avoided and engineering efforts can

directed in more fruitful directions.

Currently, building an effective decision support system can often be a rather daunting task. There are

not many tools available, and so the experience of an expert plays a major role in the development of

systems and this is often characterised by trial and error. The net effect of this is that building systems is

expensive and so can often only be undertaken by large organisations that have the required resources

to devote to these projects. This often means that computational techniques are effectively unavailable

to small and medium sized enterprises. The aim of this theme is to develop the theoretical understanding

required to underpin the construction of tools and components to allow decision support systems to be

built automatically and adapted quickly. The idea is to effectively capture much of the role that normally

requires a human optimisation or computational search expert. This is a particularly challenging goal which

is being addressed in the almost complete absence of a mathematical and theoretical understanding of

how to build intelligent systems which are capable of automatically building new systems.

Heuristic Understanding

Systems to Build Systems

A Landscape Analysis of a search space.


Next Generation Decision Support Automating the heuristic design process

The current state of the art in decision support and

search methodologies tends to focus on bespoke problem

specific systems. Such approaches could be made more

widely applicable, by automating the process of designing

problem solving techniques. Most real world decision

support systems represent vast search spaces of potential

solutions. These spaces are so large that it is usually

impossible to develop methods which can guarantee the

location of the optimal solution. In order to navigate such

enormous search spaces, the scientific community has, in

the last 30 years, increasingly turned towards the use of

heuristics and meta-heuristic methodologies (as well as

hybridisations with other approaches) to find high quality

solutions to such problems. Despite the success of meta-

heuristic methods in solving real-world computational

search problems by developing bespoke problem specific

methods, there are still some difficulties in easily applying

them to newly encountered problems, or even new

instances of known problems. These difficulties arise

mainly from the significant range of parameter or algorithm

choices when using these approaches, and the lack of

guidance on how to select them. Another drawback is that

these state-of-the-art approaches for real-world problems

tend to be expensive to develop and maintain.

The ASAP group has been awarded a £2.66m strategic

EPSRC grant which underpins our research efforts in

this area over a five year period (EP/D061571/1: Next

Generation Decision Support: Automating the Heuristic

Design Process). The potential benefits of success in such

a radical undertaking are enormous and permeate not

only the disciplines of Computer Science and Operational

Research but also the various disciplines that draw upon,

and contribute to them. These include Mathematics,

Business, Engineering, Computational Chemistry, Medicine,

Architecture (space management), Bioinformatics,

Manufacturing and all areas of Management. The

research also impacts upon automated heuristic selection

and design across many diverse applications such as

scheduling, timetabling, cutting/packing, protein folding,

catalyst optimisation, medical decision making and others.

This research initiative is investigating the development of

systems which are able to automate the heuristic design

process. A key principle behind this challenging research

goal is not only the automation of the underlying heuristic

selection process, but also the adaptation and evolution

of the higher-level algorithms, in order to respond to

changes in the problem specification or the environment.

In effect, we aim to replace the ‘knowledge engineer’ with

intelligent search based methods that can automatically

generate heuristic methodologies to suit the current

problem under consideration.

We are combining fundamental advances in the

underpinning areas of automated heuristic design, such as

Evolving 2D packing heuristics with Genetic Programming (by Matthew Hyde)

6 A S A P

Self-assembling hyper-heuristics for the travelling salesman problem (by German Terrazas)

machine learning, fuzzy systems, cooperative techniques,

and genetic programming with risky, exploratory research

into more adventurous areas such as software self-

assembly, in order to progress the automation of designing

heuristics. In this major undertaking, we are pulling

together, sometimes diverse strands, which we believe to

be complementary but which have often only been studied

in isolation. This is being undertaken in a wide range of

original investigations and novel hybridisations in order to

bring about a step change in decision support and search

methodologies – in short, the next generation of decision

support techniques.

In addition to the £2.66m grant, this major, strategic research

direction is supported by other EPSRC awards including:

Optimisation Methods in Health Care Planning • (Research Council of Norway):

£1m (£940K SINTEF and £60K Nottingham)

PLATFORM: Towards More General Optimisation/• Search Systems (EPSRC: GR/S70197/01):

£423K (Nottingham)

Genetic Programming in a Hyper-heuristic Framework • (EPSRC: EP/C523385/1):

£475K (£228K Nottingham, £247K Essex)

Hyper-heuristics for Scheduling, Rostering and Routing • (EPSRC: EP/C547377/1):

£32K (Nottingham and Montreal)

Moreover, the work is being theoretically underpinned

by the “Systems to Build Systems” theme of the LANCS

Initiative (see page 5).


Timetabling is a difficult real world problem faced by many institutions all around the world.

ASAP maintains a leading role in timetabling research. The International Conference on the Practice and

Theory of Automated Timetabling (PATAT) is a biannual conference series that has been co-organised

by the ASAP research group since the series started in 1995. PATAT conferences provide a forum for

timetabling researchers and practitioners to share their ideas and experiences.

ASAP has also been leading the Association of European Operational Research Societies (EURO)

Working Group on Automated Timetabling (WATT) since 1996. Biannual workshops that complement the

PATAT conferences have been organised in alternating years within the EURO and IFORS conferences. A

digest of up-to-date timetabling news has been distributed at regular intervals to the WATT members.

A discussion list has been maintained for promoting timetabling research and providing a medium for

WATT members to exchange their ideas and opinions.

ASAP played a key role in organising the second International Timetabling Competition 2007, held

in collaboration with Queen’s University Belfast, Cardiff University, Edinburgh Napier University and

the University of Udine. The competition, consisting of three tracks covering examination and course

timetabling, received international attention and many submissions from across the world. The successful

approaches for each track were published in the PATAT2008 Proceedings.

In addition to our work on organising international meetings and events, the ASAP group investigates

the following topics at the cutting edge of timetabling research:

Compilation and modelling of new examination and course timetabling problems that capture real • world complexities

Development of intelligent computational search methodologies, such as, heuristics, meta-heuristics • and their hybrids for solving single and multi-objective real world timetabling problems, having a

rich set of features and constraints

Explanation of novel adaptive approaches, such as hyper-heuristics that can operate at a higher level • of generality than the current timetabling systems can support

Problem representation issues in timetabling• Investigation of the effect of different component choices for learning hyper-heuristics on their • performances and comparison of hyper-heuristics for timetabling and other problems

Integration of exact methods, such as integer programming and constraint programming with meta-• heuristics for solving large and highly constrained timetabling problems

The ASAP group’s world-leading into automated timetabling underpins the commercial activity of one

of its spinout companies EventMap Ltd (see page 22).

Timetabling

8 A S A P

Many sporting events are structured as a round robin tournament

(where every team plays every other team), or as a double round

robin tournament (where every team plays every other team twice;

once at their home venue and once at the other team’s venue).

Other events are based on a knockout structure where a team is

eliminated from the competition once they have lost. Some events,

such as the football World Cup, combine elements of a round robin

tournament, followed by a knockout stage.

Although the algorithm to produce a (double) round robin

tournament is well known, the generation of a feasible fixture list is

often complicated by the many additional factors that have to be

taken into account.

Within the research group, we have focussed on the double round

robin tournament for the English football league. In particular, we

have addressed a subset of the problem which aims to minimise the

travel time for supporters over the Christmas/New Year period.

The fixtures that are played at this time of the year have been

constructed with the goal of having the minimal travel time when

compared against other dates in the calendar. We have demonstrated

that we are able to further reduce the travel distances when compared

to the fixtures that are published by the football authorities.

We are currently extending this work in a number of ways.

For example:

Improving the search methodology that is utilised.• Investigating the multi-objective aspects of the problem. • That is, still trying to minimise the distance travelled by the

supporters but also reduce policing costs by limiting the number

of local derbies.

Scheduling a sequence of four matches over the Christmas • period, while still minimising the travel distances. This is

important during World Cup years when efforts are made to

shorten the season.

There are many other sports scheduling problems, such as • referee assignment, which do not fall into the category of round

robin or knockout tournaments, but which represent complex

scientific challenges.

Sports Scheduling

Notts County Football Ground: The oldest football club in the world (Graham Kendall)

9 www�asap�co�uk

Cutting and packing problems impact upon a broad range of

industries where the efficient usage of space or material is an

important consideration within the manufacturing life cycle. For

industries such as textiles, automobile production and aerospace

(amongst others), even a small reduction in the material required to

produce each product or component can translate into significant

cumulative cost savings along with a real environmental impact in

terms of more efficient use of resources.

ASAP has carried out leading edge research into two-dimensional

cutting and packing problems for well over a decade and has

published some of the best performing heuristic and meta-heuristic

algorithms within the literature for both rectangular and irregular

variants of the problem. More recently, ASAP has added three-

dimensional problems to its research portfolio and continues to

publish novel approaches that are producing some of the best-

known solutions on benchmark instances.

Due to the success of ASAP’s research into cutting and packing

problems, Aptia Solutions Ltd (a spin-out company) was

formed to further develop these approaches and explore other

commercialisation opportunities. This has lead to the development

of a number of new products which are increasingly being adopted

by a wide variety of industries.

Many of the research challenges, when developing cutting and

packing algorithms, arise due to the underlying geometry that has

to be dealt with. Our work on the No Fit Polygon has provided other

researchers with algorithms to utilise this important data structure. We

have also reported the benefits of using an efficient implementation

of the No Fit Polygon in some of our other publications.

We have held a variety of awards which have funded our work in

cutting and packing. These include PLATFORM: Towards More

General Optimisation/Search Systems (GR/S70197/01), Next

Cutting, Packing and Space Management

One of the products developed by our spin-out company, Aptia Solutions Ltd: Simulation of a cutting machine

10 A S A P

Generation Decision Support: Automating the Heuristics Design

Process (EP/D061571/2) and An Investigation of Cutting/

Packing and Planning using Automated Algorithm Selection (GR/

S52414/01).

Space allocation is concerned with making the most effective use

of the space available. This might be office space, university lecture

halls, academic offices etc. Our work in this area is underpinned by

an EPSRC award entitled Adaptive Multi-objective Heuristic and

Meta-heuristic Approaches to Space Planning (GR/T26115/01).

This project largely focussed on university teaching space allocation.

Within educational institutions, teaching space is an expensive

resource to provide and maintain. Providing too much space will be

costly, providing too little space or an inappropriate mix of room

sizes and facilities could negatively impact the satisfaction amongst

both staff and students. Our work on space allocation has provided

new methods to handle this delicate balance. It has been based

on novel uses of the theory of thresholds and phase transitions

to explain how the properties of systems can change rapidly with

seemingly mild changes in their characteristics.

Our work in cutting, packing and space allocation has benefited

from an EPSRC NETWORK award called NETWORK: Interdisciplinary

Cutting, Packing and Space Allocation (EP/D031079/1) which,

amongst many other activities enabled us to organise a Dagstuhl

seminar on Cutting, Packing and Space Layout (Seminar 07112),

which led to selected papers being published in a special issue of

Annals of Operations Research.

Aptia Nest

“ Our work in this area is

underpinned by an EPSRC

award titled as Adaptive

Multi-objective Heuristic and

Meta-heuristic Approaches to

Space Planning.”

London Heathrow is one of the busiest airports in the world,

having more international passengers than any other airport. The

sequencing of departures at the runway is an important but complex

problem which directly affects the delay for outbound flights.

However, this problem is currently solved manually by a runway

controller in the control tower at Heathrow. Although the controllers

perform excellently (simulations indicate that delays would be over

four times as long without the re-sequencing performed by the

controllers), with up to one take-off a minute, there is insufficient

time for controllers to consider all possible good take-off sequences.

Funded by EPSRC and NATS (formerly National Air traffic Services)

Ltd, through the Smith Institute for Industrial Mathematics, the

ASAP group has investigated the feasibility of harnessing the

power and flexibility of modern computational search techniques

to provide accurate advice to controllers via an intelligent decision

support system. The aim is to provide the controllers with the

information which would be necessary to enable them to reduce

delay even further. This involves considering not only the value of

a take-off sequence, but also whether it can be attained and how

hard the manoeuvring on the ground would be to attain it. The

challenge for developing such a decision support system is not only

to provide accurate advice, but also to do so quickly enough so

that the controllers are able to respond immediately to situational

changes at this popular and busy airport. The algorithms which

have been developed are fast enough to find lower delay take-off

sequences in less than a second.

Reducing delay at the runway is good for passengers, airlines and

the environment, but the throughput of the runway is limited.

Queues can, therefore, sometimes accumulate no matter how good

the scheduling is. To further reduce the environmental impact at

the airport, another ASAP project, again funded by NATS and

EPSRC, considers the advantages of holding aircraft on the stands,

before their engines are started, rather than at the runway. This

decision support system considers all of the aircraft at the airport,

predicts the likely take-off times (and the consequent delay), then

absorbs as much delay as possible at the stand by delaying the

pushback time from the stand, where necessary. The difficulty here

is that, not only do the take-off sequence restrictions have to be

considered, but so do issues of contention between aircraft which

are at stands which are close together. It is impossible for aircraft

to simultaneously push back from some combinations of stands,

and there are other combinations where one aircraft would be

blocked by another and would have to wait for it to move out of

the way before it could start its own pushback. Simulations using

the developed system have shown considerable decreases in engine

Scheduling in the Air Transport Industry

12 A S A P

running time, thus, NATS are planning to integrate the system

into Heathrow soon. In both of these cases, the problem under

consideration is too large to solve exactly within the permitted

time-frame, but our innovative modelling and heuristic techniques

make it possible to produce algorithms to find high quality solutions

quickly enough for practical use.

The ASAP research group has also worked in close collaboration

with Air-France-KLM to investigate new approaches to build

more robust schedules. The approach implements minor changes

in existing schedules which help to improve robustness and

reduce passenger delays. A more robust schedule is one that

is less sensitive to disruptions on the day of operation, offers

increased flexibility to recover from disruptions, and prevents

delay propagation through increased schedule stability. The

approach developed by ASAP facilitates the investigation of

mutual interaction between multiple robustness characteristics of

a schedule and the quantification of their simultaneous influence

on the schedule’s operational performance. This research has

contributed to fundamental new insights in the robustness of airline

schedules, and a better understanding thereof. This underpins the

development of future models for robust airline scheduling. The

fundamental contribution of this research project was internationally

recognised: it was awarded the best technical innovation at the

Airline Operations Meeting of the Airline Group of the International

Federation of Operational Research Societies, Denver, Colorado,

2007 and it received second place in the Anna Valicek Competition

for innovative research in Airline Research (see http://www.agifors.

org/award_home.jsp).

The modern air transportation system is a complex environment,

where many different optimisation and search problems have to be

solved every day. Further currently planned research (supported

by EPSRC, NATS and both Manchester and Zurich airports) will

cover the integration of the arrival sequencing problem, the stand/

gate allocation problem and modelling and optimisation of other

ground processes at Manchester, Zurich and other airports. Again,

the emphasis is to consider the real problems that are faced at

real airports, in order to obtain real benefits for airports, airlines,

passengers and the environment.

The number of cancer cases in the United Kingdom has continually

increased in the last few decades. Every year, 200,000 people are

diagnosed with cancer in England and 120,000 people lose their

lives to the disease. Efficient radiotherapy planning and resource

management in oncology departments has been recognised as a key

factor to their smooth running. The various activities, starting from

patient referral through to the delivery of the appropriate treatment,

form a complex system, for which generating a high quality planning

and scheduling solution is a challenging real-world problem that has

significant impact on healthcare staff and patients.

We are carrying out an ambitious research program on radiothearpy

planning and scheduling supported by EPSRC (EP/C549511/1:

Novel Approaches to Radiotherapy Planning and Scheduling in the

NHS). This is a joint research project with Coventry University.

Two large hospitals, Nottingham University Hospitals NHS Trust and

the University Hospitals Coventry and Warwickshire NHS Trust, are

acting as collaborators on the project. Both of them are providing

radiotherapy treatment to a large population throughout their

respective regions.

This research requires a multidisciplinary effort, aiming to

combine different Operational Research and Artificial Intelligence

methodologies within a complex real-world medical environment.

The main objectives of the project are:

1. To develop a prototype intelligent decision support system

to assist oncologists and medical physicist, in the generation of

radiotherapy treatment plans for patients. In a substantial part of

the published literature on radiotherapy, treatment planning has

been set as an optimisation problem where the objectives are to

achieve a uniform tumoricidal dose and to minimise the radiation

dose received by organs at risk and by healthy surrounding tissue.

However, all of the proposed approaches start from scratch in

creating a plan for each patient, rather than understanding a new

problem in terms of old cases. Our aim is to explore new directions

Healthcare Modelling and Optimisation

A plan for a radiotherapy treatment for brain tumor

14 A S A P

in radiotherapy planning, which use the knowledge and experience

gained in solving previous problems to address treatment planning

for new patients. So far, we have developed a case-based reasoning

system for prostate cancer planning which aids in determining the

dose plan for a new patient, by using the knowledge and experience

of an oncologist gained in treating previous patients. Also, we are

working with medical physicists to develop a system which will assist

in the planning of brain tumour treatments.

2. To develop a prototype decision support system to assist

in scheduling resources in radiotherapy. In this area, patient

scheduling has been recognised as a key factor for increasing the

quality of treatments, as it is of paramount importance to deliver

the treatment by the imposed waiting time target and to enable

consecutive treatment sessions without interruptions. Before

starting a radiotherapy treatment, a patient needs to go through

several phases, including the localisation of treatment fields using

a CT scanner or simulator, radiotherapy planning in which the

dosage and the best way to deliver radiation is determined and

the verification of a plan using a simulator. We develop systems for

both the scheduling of pre-radiotherapy phases and the scheduling

of patient sessions on linacs (linear accelerators). Our research on

radiotherapy scheduling was awarded a Certificate of Merit at the

International Conference on Intelligent Automation and Robotics,

within the World Congress on Engineering and Computer Science

(WCECS’08) in 2008.

Our system for radiotherapy scheduling provides the user with a friendly

windows-based interface

Another key area for the research group is in the development of

staff rostering methodologies and systems for health care. Some of

the most complex and challenging duty allocation problems arise in

hospitals and healthcare centres, for example nurse and physician

rostering. The benefits of automating the rostering process in these

situations include reducing the planner’s workload and associated

costs and being able to create higher quality and more flexible

schedules. This has become more important recently in order to

retain nurses and attract more people into the profession. Better

quality rosters also reduce fatigue and stress due to overwork and

poor scheduling and help to maximise the use of leisure time by

satisfying more requests. A more contented workforce leads to

higher productivity, increased quality of patient service and a better

level of healthcare. The ASAP group has developed a number of

novel and successful rostering algorithms for real world scenarios.

These approaches include tabu search, variable neighbourhood

search, memetic algorithms, case-based reasoning, hyper-heuristics,

hybrid methods and many others. In order to scientifically test

and validate these algorithms, we have created a suite of highly

challenging benchmark data sets from a number of hospitals around

the world. These data sets are publicly available at

http://www.cs.nott.ac.uk/~tec/NRP/.

In developing new algorithmic approaches, we often work closely

with industrial and non-academic partners. For example, in one of

our ongoing projects we are collaborating with SINTEF (the largest

independent research organisation in Scandinavia) on producing

more robust algorithms and flexible models for nurse rostering

through the application of hyper-heuristics.

Roster Booster – a modelling tool, solver and solution viewer for nurse rostering


In most real-life modern environments, scheduling is an ongoing

process where circumstances in both external business environments

and in internal production environments may dynamically change. In

order to ensure high customer service level and profitability, there is a

need to respond to disturbances such as machine breakdowns, delays

in the arrival of materials, the arrival of rush orders and changes in

orders. The goal then is to modify the existing schedules, either to

restore their feasibility or to produce a higher quality schedule.

We are continuing our collaboration with Sherwood Press, a printing

company based in Nottingham. This collaboration started with

an EPSRC funded project (GR/R95319/01: Fuzzy Multicriteria

Approaches to Scheduling and Rescheduling Problems in Uncertain

Environments) which investigates the problem of integrating

new orders into the current schedule. The aim is to obtain a new

schedule with a good performance which is at the same time

stable, i.e. it resembles the initial schedule as closely as possible. In

particular, we have developed matchup algorithms, which define a

rescheduling horizon within which to schedule operations required

by a new order, enabling the remaining part of the initial schedule

to stay unchanged. Our research was awarded the best paper award

at the 21st International Conference on Industrial, Engineering &

Other Applications of Applied Intelligent Systems (IEA\AIE) in 2008.

Production Scheduling

Sherwood PressOver the last decade, fully automated manufacturing systems have

enormously increased the flexibility and efficiency of the production

process. In these flexible manufacturing systems, the material

(jobs) can be moved between machines automatically with the help

of transport robots (guided vehicles). In addition to the regular

problem of job shop scheduling, the transport of jobs between the

machines has to be planned ahead. Our aim, in another challenging

research direction, is to find efficient methods to solve the problem

of cyclic scheduling and transportation as an integrated operation.

Our prototype system for scheduling provides a user-friendly windows-based interface

16 A S A P

Data mining for BioinformaticsWe are carrying out an innovative and ambitious research

programme at the interface of data mining and bioinformatics.

Recent advances have demonstrated the potential for success in

developing ever more general, intelligent and reliable classification

and predictive technologies. We are exploring the feasibility of

designing and implementing robust classification and predictive

systems that can deliver high quality bioinformatics predictions

while making these predictions human-understandable. We

have built Array Mining, a server for automatic analysis of DNA-

microarray data. It provides a combination of three web interfaces

dedicated to three major tasks in gene expression analysis: Feature

selection (Gene Selection), Clustering (Class Discovery) and

Prediction (Class Assignment). Array Mining performs automatic

parameter selection, generates tabular and visual outputs (e.g. 2D-

and 3D-VRML plots) as well as links to public online data bases to

make functional gene annotations available with only a few mouse

clicks. We have also produced the following cutting edge learning

classifier systems that are capable of dealing with extremely large,

noisy and ambiguous bioinformatics data-streams.

PSP-Server, predicts geometrical features in proteins’ • native 3D structure

ArrayMining, provides a sophisticated algorithmic pipeline for • analysing DNA microarray data.

The ASAP research group is exploiting exciting Multi-disciplinary

synergies with the School of Chemistry, the Center of Bio-molecular

Sciences, the School of Pharmacy and the School of Life Sciences.

All these collaborations are performed under the umbrella of the

Inter-disciplinary Optimisation Laboratory. Our activities cover the

three themes of Structural Bioinformatics, Data mining, Systems

Biology and the emerging field of Synthetic Biology. Our software is

publicly available at www.infobiotic.net.

Structural BioinformaticsFunded through various ESF, BBSRC and EPSRC grants (e.g.

ESF-2482, EP/E017215/1, GR/T07534/01, BB/C511764/1), the

ASAP group carries out research at the cutting edge of structural

bioinformatics. We have developed ProCKSI, a decision support

system for protein structure comparison that computes structural

similarities using a variety of measures to produce a consensus. It

contains tools for visualising, analysing and easily comparing all

results, linking to external resources for further information and

literature about protein structures. These services are part of a

greater investigation of a suitable framework/architecture for very

large scale protein structure comparison, clustering and analysis

in parallel and distributed environments, involving the evaluation

and selection of, optimal middleware software, database model,

programming libraries, tools and algorithms.

We have also developed a Protein Structure Feature Prediction

server containing a collection of web services that use learning

classifier systems to predict Protein Structure Prediction (PSP)

sub-problems such as coordination number, solvent accessibility or

recursive convex hull. These subproblems are structural features of

protein residues that contain information about the end product

of the folding process. These features are related to the density of

packing of different parts of a protein or how buried/exposed,

far/close to the surface are different residues within a protein.

Bioinformatics, Systems and Synthetic Biology


Systems Biology and Synthetic BiologySystems Biology seeks to achieve an integrative, quantitative

understanding of biological systems spanning multiple length,

time and organisational scales from the subcellular, to the cellular,

colony/tissue scales all the way to ecological levels. On the other

hand, Synthetic Biology (an emerging discipline) seeks to produce

robust and reliable computational/mathematical techniques to

calculate or compute, based on a set of phenotype requirements,

the experimental route to their wet lab implementation. We are

developing an in-house methodology, InfoBiotics, that could

deal with the multiple challenges facing Systems and Synthetic

Biologists. Infobiotics, funded from multiple sources (e.g., EP/

E017215/1, BB/D0196131) is the synergy of executable biology,

evolutionary and machine learning methods, mesoscopic simulation

techniques and experimental data for a more principled practice

of origins of life, bioinformatics, computational systems and

synthetic biology research. P systems, computing with membranes,

abstract the structure and function of the living cell into a

formalism upon which we are building a multi-scale modelling

environment. By applying discrete, numerical simulation algorithms

to P system models of quorum sensing in the bacterial pathogen

Pseudomonas aeruginosa and root development in Arabidopsis

thaliana, we aim to understand the stochastic processes governing

these model organisms in order to guide laboratory experiments.

In addition, we use evolutionary search and machine learning

(Genetic Programming, Learning Classifier Systems, Support Vector

Machines, etc) to estimate parameters and discover structures that

match observed behaviour in cellular networks with the intention of

isolating these modules for use in the design of synthetic organisms.

Dissipative Particle Dynamics underpins our simulation of (proto-)

membranes. These activities are complemented by other groups

in the SynBioNT Synthetic Biology Network for Modelling and

Programming Cell-Chell Interactions (BB/F01855X/1) and The

CHELL: A Bottom-Up approach to in vitro and in silico Minimal Life-

like Constructs (EP/G042462/1).

The InfoBiotics pipeline includes complex combinatorial, continuous

and mixed discrete/continuous optimisation of systems/synthetic

biology models as well as a state-of-the-art simulator, model

checking capabilities and cutting-edge user interface.

The InfoBiotics pipeline

18 A S A P

EP/D021847/1: Chemical Craftwork: Evolvable CHELLware

Principal Investigator: Natalio Krasnogor

In a wide range of fields, computer algorithms which mimic an

evolutionary (or Darwinian) strategy are finding many applications,

particularly in the field of evolvable hardware where field

programmable gate arrays can be ‘constructed’ by evolutionary

programs to perform complicated tasks. This project is based on

the analogous idea of using evolutionary algorithms to develop

chemical functionality in arrays of ‘programmable’ chemical

reactors, based on current lab-on-a-chip and electrochemical cells.

In the future, we hope to apply these methods to complex reactors

built in artificial vesicles which communicate by chemical signals

much like a living cell. This project is closely linked with a network

grant (EP/D023343/1; CHELLnet: A Unifying Investigation in

Artificial Cellularity and Complexity) which was funded from the

same IDEAS factory.

EPSRC IDEAS FactoriesASAP researchers have been successful participants of a number of

EPSRC IDEAS Factories, which are based around a ‘sandpit’ event

where researchers from a variety of institutions and disciplines

meet to discuss innovative research ideas around a common theme.

ASAP’s interactions with these events have led to the following

funded projects.

EP/E017975/1: An Investigation of

Regulatory Decision Making by Automated Decision Makers

Principal Investigator: Graham Kendall

This project comprises a multi-disciplinary, inter-institutional team

drawn from Computer Science (Nottingham), Psychology (London

School of Economics) and Industrial and Manufacturing Science

(Cranfield). A two-year research assistant (based in Nottingham) is

supported by a PhD student based at Cranfield.

The project is modelling regulatory decision making environments,

including salt intake, nuclear waste disposal and avian flu and it is

studying how personality and power influences the decision

making process. Interviews with the decision makers have provided

input to a computer simulation which is exploring whether or not

we are able to mimic the decisions that were actually made. The

simulation environment draws heavily from the psychology literature

in modelling personalities and the power structures that exist in

group decision making.

EP/H004424/1: Integrating and Automating Airport Operations

Principal Investigator: Edmund K� Burke

This project represents a wide ranging multi-disciplinary and

cross-institutional initiative to exploit recent research advances

in automated search methodologies and decision support

techniques for airport operations. The proposed programme of

research will build integrated computational models of four key

airport operations: take-off scheduling, landing scheduling, gate

assignment and baggage flow. The project will explore how to

build computational models that represent the integration of

these problems and it will explore how to develop effective

multi-objective search methodologies which will employ those

models. Integrating these four operations and exploring new

and exciting ways of generating high quality solutions to the

integrated problem is the broad basic aim of the proposal. We

will work closely with colleagues at Manchester and Zurich

airports to ensure that we have continuous access to real world

expertise and data.


The ASAP group carries out interdisciplinary research in collaboration

with researchers and practitioners from a wide range of different

backgrounds. Our existing research themes cover Computer Science,

Artificial Intelligence, Operational Research, Biology, Chemistry,

Psychology and many more. We work, and publish, with scientists

from many different countries including Australia, Belgium, Canada,

China, France, Germany, Iceland, Italy, Malaysia, Norway, Poland,

Spain, The Netherlands, Turkey and USA. We maintain fruitful

partnerships with the leading scientists in the UK and beyond,

through scientific networks and visiting fellowships. In addition to

the visiting fellowship grants held by the group, many self-funded

leading researchers from all over the world visit the group to engage

with the high quality research carried out within ASAP.

Members of the ASAP group have key editorial roles in many

of the leading journals in our areas, including Evolutionary

Computation, IEEE Transactions on Computational Intelligence and

Artificial Intelligence in Games, IEEE Transactions on Evolutionary

Computation, INFORMS Journal on Computing, Journal of

Heuristics, Journal of Scheduling and Memetic Computing. Many

members of the group are also represented on the program

committees of the leading conferences in our areas.

ASAP has established two international conferences:

MISTA (Multidisciplinary International Conference on • Scheduling: Theory and Applications) has been run in 2003,

2005, 2007 and will be run in Dublin in 2009.

PATAT (Practice and Theory of Automated Timetabling) has • been run in 1995, 1997, 2000, 2002, 2004, 2006, 2008. The

2010 conference will take place in Belfast.

The strength of our outreach capacity is further reflected by the

continuous success of the group in transferring and commercialising our

research findings. The group has three spinout companies (Event MAP

Ltd, Aptia Solutions Ltd and INFOHUB Ltd). It also collaborates with

a number of other industrial partners including Air France, BT Group,

Denby Pottery Company Ltd, DIPS ASA, GAT-Soft AS, Gower Optimal

Algorithms Ltd, KLM, Merlin Systems Corp Ltd, NATS, Nottingham City

Hospital, Ortec, Realtime Solutions Ltd, Sherwood Press and Walsgrave

General Hospital. Moreover, the group holds two recently awarded

Knowledge Transfer Partnership grants (with Midland Software Ltd

and 3T Logistics Ltd). ASAP also covers postgraduate research training

and public communication by involvement in initiatives aimed to

improve the provision of high quality taught courses for PhD students.

Moreover, the group is committed to raaising public awareness about

our scientific research and its impact on industry and businesses.

Visiting FellowshipsASAP continues to collaborate with many leading scientists from

around the world. These collaborations have been underpinned by

EPSRC Visiting Fellowships that the group has held since 2002. This

has enabled regular visits by:

Moshe Dror (GR/S07124/01) 2002-2003• Jacek Blazewicz (GR/S64530/01) 2003-2007• Amon Meisels (GR/S53459/01) 2003-2004• Michel Gendreau (EP/D027039/1) 2006-2011• Peter Brucker (GR/T23374/01) 2004-2009•

NATCORThe ASAP group plays a leading role in the NATCOR (A National

Taught Course Centre in Operational Research) initiative which

aims to improve the provision of high quality taught courses in

Operational Research for PhD students. NATCOR is funded by

EPSRC for the first five years of its life (October 2006 to September

2011) and is supported by the Operational Research Society which

is a collaborating partner.

Outreach

ASAP is collaborating with Prof

Peter Brucker through an EPSRC

Visiting Fellowship award and other

collaborative grants.

Prof David Goldberg giving a seminar

during his ASAP visit

20 A S A P

Internationalisation ASAP now has representation at both of our international campuses

in Malaysia and China. Ruibin Bai (China), Andrzej Bargiela

(Malaysia) and Siang Yew Chong (Malaysia) play an active role in

the research group, supported by close collaboration with ASAP

personnel at all three campuses. The MNDP (Malaysia Nottingham

Doctoral Program) also supports exchanges between ASAP and

colleagues in Malaysia. A recent Chinese government award has

enabled this level of research activity to be further increased.

Knowledge Transfer PartnershipsThe group has recently been awarded two Knowledge Transfer

Partnership (KTP) grants to further develop and apply our search

and optimisation technology for the benefit of companies in our

region. The KTP programme (http://www.ktponline.org.uk/) is a

high profile government initiative to fund the transfer of knowledge,

technology and skills to SME’s to help them become more

competitive and efficient. Our two projects can be outline as follows:

KTP 7074 is a partnership with Midland Software Limited • (http://www.midlandhr.com/), a company that provides a

range of HR Management solutions, to develop a personnel

scheduling engine.

KTP 7449 is a partnership with 3T Logistics Limited, a company • that provides outsourced transport solutions, to develop an

automated carrier management and scheduling system.

Both of the above projects will have duration of two-years and

are tangible evidence of our capacity to transfer the expertise and

technology developed within the ASAP group to the real-world.

The Interdisciplinary Optimisation Laboratory (IOL) The IOL is a multi-disciplinary research institute at the University

of Nottingham. The lab is based on the Jubilee Campus, in the

School of Computer Science and is closely linked to the Automated

Scheduling, Optimisation and Planning Research group (ASAP).

The IOL carries out inter-disciplinary research across the fields of

Computer Science, Biology, Chemistry, Physics, Management Science,

Mathematical Sciences, Medical Sciences, Psychology and Robotics.

In particular, it focuses on developing innovative and competitive

search methodologies and intelligent decision support systems with

an emphasis on transdisciplinary computational search, the modelling

of complex systems and very-large datasets processing.

Some of the IOL current projects include collaborations with Prof.

P. Moriarty and Prof. P. Beaton from the School of Physics and

Astronomy on the optimization of scanning probe microscopy

procedures. With Prof. N. Champness and Prof. J. Hirst in the

School of Chemistry, the IOL investigates optimisation strategies

for designing molecular tiles and protein structures respectively.

The IOL also carries out research at the cutting edge of systems and

synthetic biology in collaboration with Prof. M. Camara and Prof.

P. Williams at the Centre for Biomolecular Sciences, with Prof. C.

Alexander in the School of Pharmacy, Prof. C. Hogman and Prof.

M. Bennett in the School of Biosciences. With Dr. N. Russell at the

Schools of Biology and Electrical and Electronical Engineering, IOL

researchers are developing unconventional computing paradigms

based on photo-switching molecular constructs.


Spin Out Companies and Knowledge Transfer PartnershipsEventMAP (see www.eventmap-uk.com) is a joint venture

between the University of Nottingham and Queen’s University

Belfast. An innovative example of fusion between research and

practice, this spin out company specialises in Institutional Strategic

Resource Planning. The company provides business analysis,

methodology and software product to allow for more effective

usage of organisational resource. The company currently deploys

the state-of-the-art Optime Scheduling Engine within their unique

‘Optimisation in Practice’ methodology. Currently, solutions are

available for the purposes of timetabling and resource planning

software solutions for the challenging problems faced by today’s

educational institutions in the areas of lecture and room scheduling,

noncurricular events scheduling and examinations scheduling. At

the heart of EventMAP’s solution provision is the integration of

leading edge research based scheduling techniques which have

the capability of providing significant institutional cost savings

through more efficient and more satisfactory use of resource.

Through the development of an innovative partnering business

model, Staff at EventMAP have implemented solutions in Europe,

New Zealand, Australia, America, Middle East, Asia and China. The

Company has also taken a leading role in helping to organise the

second International Timetabling Competition and the PATAT2010

conference in Belfast.

Aptia Solutions (see www.aptiasolutions.com) is a software

development company that has grown out of the research

developed by ASAP. It specialises in the development of powerful

yet easy to use automated nesting products for industries in which

CNC machining is an important part of the manufacturing lifecycle.

Aptia spun-out from the University of Nottingham in 2004 and

started selling the first of its commercial products in January 2008.

At the time of writing, over 80 customers rely on Aptia’s products to

support their cutting requirements and maximise material utilisation.

The powerful cutting and packing algorithms developed by ASAP

researchers underpin Aptia’s products.

INFOHUB (see www.infohub-ltd.co.uk) is a research-led

company developing system solutions for information acquisition,

processing and delivery. The company specialises in human-

centred applications such as decision support, data mining and

information services in traffic, transport and environmental sectors.

The systems developed at InfoHub enhance the value of both the

existing information sources and current and future communications

technology. The spectrum of systems ranges from information

systems for the general public through to specialised information

management tools that offer several levels of information

generalisation required to support decision-making processes in

complex systems and in the presence of uncertainty.

“ The group has recently been awarded two Knowledge

Transfer Partnership (KTP) grants to further develop and

apply our search and optimisation technology for the

benefit of companies in our region.”

22 A S A P

Professional ActivitiesEPSRC Peer Review CollegeA. Bargiela, E.K. Burke, G. Kendall, N. Krasnogor, J.D. Landa-Silva, S. Petrovic

Company DirectorshipsA. Bargiela:

Director of INFOHUB Ltd.• E.K. Burke:

Research Director of EventMAP Ltd.• Director of Aptia Solutions Ltd.•

G. Kendall:

Director of EventMAP Ltd.• Director of Aptia Solutions Ltd.•

FellowshipsE.K. Burke:

Fellow of the British Computer Society• Fellow of the Operational Research Society•

G. Kendall:

Fellow of the Operational Research Society•

National and International Committee MembershipsA. Bargiela:

Management Board of the European Council for Modelling and Simulation (immediate past Chairman)• Visiting Professor, University of Alberta, Canada• Special visiting fellow, Konan University, Japan•

E.K. Burke:

Jury for the (EURO) Gold Medal, 2007 • EPSRC Mathematics Strategic Advisory Team for Mathematics, 2008 • Advisory Board of the EPSRC IDEAS Factory Network on Productivity• Advisory Board of the EPSRC SEBASE (Software Engineering By Automated SEarch) Initiative • Executive Committee of the EPSRC National Training Centre for Operational Research • International Advisory Board of the BBSRC/EPSRC Centre for Plant Integrative Biology • Scientific Steering Committee of the Isaac Newton Institute for Mathematical Sciences (nominated by EPSRC) • Scientific Committee of the Smith Institute for Industrial Mathematics and System Engineering • European Science Foundation (ESF) Pool of Reviewers • UK Computing Research Committee (UKCRC) • General Council of the OR Society • Education and Research Committee of the OR Society • Management Board of the EPSRC LANCS Initiative • Executive Committee of the EPSRC LANCS Initiative • Scientific Board of the Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA), 2007 (Chairman)•


G. Kendall:

Dagstuhl Seminar on Cutting, Packing and Layout, 2007 (Co-chair)•

E. Özcan:

Executive Committee of the EPSRC LANCS Initiative•

A. Parkes:

Executive Committee of the EPSRC LANCS Initiative•

S. Petrovic:

EURO (European Association of Operational Research Societies) Working group on Automated Timetabling (WATT) (Coordinator)•

Journal EditorshipsJ. Bacardit:

Guest Co-editor of a forthcoming special issue of the Memetic Computing journal on ‘Metaheuristics for Large-Scale Data Mining’.•

A. Bargiela:

Associate Editor of IEEE Transactions on Systems, Man and Cybernetics, Part A• Editor-in-chief of Modelling and Simulation in Engineering, Hindawi Press• Editorial Board of Information Sciences (Member)• Editorial Board of International Journal of Intelligent Decision Technologies (Member)• Editorial Board of Journal of Advanced Computational Intelligence and Intelligent Informatics (Member)• Editorial Board of International Journal of Knowledge Engineering Systems (Member)• Editorial Board of International Journal of Simulation: Systems, Science & Technology (Member)•

E.K. Burke:

Editor-in-chief of the Journal of Scheduling • Area Editor (for Combinatorial Optimisation) of the Journal of Heuristics published by Springer • Associate Editor of the INFORMS Journal on Computing • Associate Editor of the IEEE Transactions on Evolutionary Computation • Editorial Board of Memetic Computing (Member)• Guest Co-editor of a feature issue of the European Journal of Operational Research (EJOR ) • on ‘Evolutionary and Metaheuristic Scheduling’, 2007

G. Kendall:

Associate Editor of the Journal of the Operational Research Society• Editorial Board of IEEE Transactions on Evolutionary Computation (Member)• Editorial Board of IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games (Member)• Editorial Board of Computational Intelligence (Member)• Editorial Board of the International Journal of Systems Science (Member)• Editorial Board of Intelligent Systems in Accounting Finance and Management (Member)• Associate Editor of INFOR: Information Systems and Operational Research• Editorial Board of Cognitive Neurodynamics (Member)• Editorial Board of International Journal of Intelligent Computing and Cybernetics (Member)•

24 A S A P

N. Krasnogor:

Founding Editor-in-chief (technical) for the Memetic Computing Journal, Springer• Associate Editor for Evolutionary Computation, MIT• Editor for Modelling and Simulation in Engineering, Hindawi Publishing Corporation• Editor for Journal of Artificial Evolution and Applications (Hindawi Publishing Corporation• Guest Editor for Natural Computation, Springer, special issue on Nature Inspired Cooperative Strategies for Optimisation, 2008• Guest Editor for Natural Computation, Springer, special issue dedicated non-standard computation and biological modelling, 2008• Guest Editor for International Journal of Intelligent Systems, Wiley, special issue on Nature Inspired Cooperative Strategies • in Optimisation, 2007

D. Landa-Silva:

Editorial Board for the Memetic Computing Journal (Member)•

G. Ochoa:

Guest Co-editor of a forthcoming special issue of the Journal of Heuristics on ‘Hyper-heuristics in Search and Optimisation’, 2008•

E Özcan:

Associate Editor of International Journal of Applied Metaheuristic Computing• Guest Co-editor of a forthcoming special issue of the Journal of Heuristics on ‘Hyper-heuristics in Search and Optimisation’, 2008•

S. Petrovic:

Guest Co-editor of the special issue of Annals of Operations Research on ‘Personnel Scheduling and Planning’, 2007• Editorial Board of the Yugoslav Journal of Operations Research - YUJOR (YU ISSN 0354-0243) (Member)•

R.Qu:

Guest Co-editor of a forthcoming special issue of the Journal of Scheduling on ‘Artificial Intelligence Planning and Scheduling’, 2008•

Conference/Workshop Organisation

J. Bacardit:

Co-chair of the 10th International Workshop on Learning Classifier Systems, London, July 8th, 2007• Co-chair of the 11th International Workshop on Learning Classifier Systems, Atlanta, July 13th, 2008•

A. Bargiela:

Management Board for ECMS’2007 (Member)• Management Board for ECMS’2008 (Member)•

E.K. Burke:

Co-chair of the Programme Committee of the 7th International Conference on the Practice and Theory of Automated Timetabling • (PATAT’08), held in Montreal, August 2008.

Co-chair of the Programme Committee of the IEEE 2007 Computational Intelligence in Scheduling Symposium (CIS 2007) in conjunction • with 2007 IEEE Symposium on Computational Intelligence (SSCI 2007), April 1-5, 2007, Honolulu, Hawaii, USA


G. Kendall:

Technical Co-chair of the Congress on Evolutionary Computation 2007 (CEC’07), September 25-28, Singapore• Co-chair of the IEEE 2007 Computational Intelligence in Scheduling Symposium (CIS 2007) in Conjunction with 2007 IEEE Symposium • on Computational Intelligence (SSCI 2007), April 1-5, 2007, Honolulu, Hawaii, USA

Co-chair of the MISTA 2007 (The 3rd Multidisciplinary International Conference on Scheduling : Theory and Applications) conference, • 28-31 August 2007, Paris, France

N. Krasnogor:

First European Conference on Synthetic Biology (ECSB I), held in Sant Feliu de Guíxols, Spain, 2007• Second International Workshop on Nature Inspired Cooperative Strategies for Optimisation (NICSO II), held in Sardinia, Italy, 2007• Third International Workshop on Nature Inspired Cooperative Strategies for Optimisation (NICSO III), held in Tenerife, Spain, 2008• First International Symposium on Embodied Evolution (EmboEvo), held in Venice, Italy, 2007•

D. Landa-Silva:

Co-chair of the Stream on ‘Timetabling and Rostering’ at the EURO 2007 Conference held in Prague, July 2007.•

G. Ochoa:

Co-organiser of the Workshop on ‘Hyper-heuristics’, held in conjunction with the PPSN X, 2008•

E Özcan:

Co-organiser of the Workshop on ‘Hyper-heuristics’, held in conjunction with the PPSN X, 2008•

Conference Programme Committee Memberships (2007-2008)J. Bacardit: 14

R. Bai: 5

A. Bargiela: 8

E.K. Burke: 24

S. Y. Chong: 1

G. Kendall: 39

N. Krasnogor: 27

D. Landa-Silva: 5

G. Ochoa: 5

E. Özcan: 8

S. Petrovic: 12

R. Qu: 6

26 A S A P

Books 2008Bacardit J., Bernadó-Mansilla E., Butz M.V., Kovacs T., Llorà, X., and Takadama K. (eds.), Learning Classifier Systems. 10th International

Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007,

Revised Selected Papers, Lecture Notes in Artificial Intelligence 4998, Springer, 2008.

Cutello V., Krasnogor N., Pavone M., and Pelta D. (eds.), Nature Inspired Cooperative Strategies for Optimization (NICSO 2007),

Studies in Computational Intelligence 129, Springer, 2008.

Krasnogor N., Gustafson S., Pelta D. A., and Verdegay J. L. (eds.), Systems Self-Assembly: Multi-Disciplinary Snapshops,

Volume 5, Elsevier, 2008.

2007Baptiste P., Munier A., Kendall G., and Sourd F. (eds.), Proceedings of the MISTA 2007 (The 3rd Multidisciplinary International Conference

on Scheduling : Theory and Applications), Paris, France, 2007.

Burke E., and Rudova H. (eds.), Practice and Theory of Automated Timetabling VI: Selected Revised Papers from the 6th International

Conference on the Practice and Theory of Automated Timetabling, Brno, Czech Republic – Lecture Notes in Computer Science 3867,

35-252, Springer Berlin / Heidelberg, 2006 – 2007.

Kendall G., Yao X., and Chong S. Y. (eds.), The Iterated Prisoners’ Dilemma 20 Years On, Advances in Natural Computation 4,

World Scientific, Singapore, 2007.

Kendall G., Burke E., Tan K. C. and Smith S. (eds.), Proceedings of the 2007 IEEE Symposium on Computational Intelligence

in Scheduling, 2007.

Book chapters 2008Atkin J., Burke E., J.Greenwood , and Reeson D., A Meta-Heuristic Approach to Aircraft Departure Scheduling at London Heathrow Airport, In

Computer Aided Systems in Public Transport (M.Hickman P. and S.Voss , Eds.), Lecture Notes in Economics and Mathematical Systems 600,

235-252. Springer, 2008.

Bacardit J., Bernadó-Mansilla E., and Butz M., Learning Classifier Systems: Looking Back and Glimsing Ahead, In Learning Classifier Systems.

10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th International Workshop, IWLCS 2007, London, UK,

July 8, 2007, Revised Selected Paper, Lecture Notes in Artificial Inteligence 4998, 1-21. Springer, 2008.

Bacardit J., and Krasnogor N., Empirical evaluation of ensemble techniques for a Pittsburgh Learning Classifier System, In Learning Classifier

Systems. 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th International Workshop, IWLCS 2007,

London, UK, July 8, 2007, Revised Selected Paper, Lecture Notes in Artificial Inteligence 4998, 255-268. Springer, 2008.

Bacardit J., Stout M., Hirst J. D., and Krasnogor N., Data Mining in Proteomics with Learning Classifier Systems, In Learning Classifier

Systems in Data Mining (Bull, L., Bernado-Mansilla, E. and Holmes, J., Eds.), Studies in Computational Intelligence 25/2008, 17-46.

Springer Berlin / Heidelberg, 2008.

Publications (2007-2008)


Landa-Silva D., and Le K. N., A Simple Evolutionary Algorithm with Self-Adaptation For Multi-Objective Nurse Scheduling, In Adaptive and

multilevel metaheuristics (Cotta S. M., C. and Srensen K. e., Eds.), Studies in Computational Intelligence 136, 133-155. Springer, 2008.

Moratori P., Petrovic S., and Vázquez-Rodríguez A., Match-up Strategies for Job Shop Rescheduling, In New Frontiers in Applied Artificial

Intelligence (Nguyen N. T., Ed.), Lecture Notes in Artificial Inteligence 5027, 119-128. Springer-Verlag, 2008.

2007Abdullah S., Burke E. K., and McCollum B., Using a Randomised Iterative Improvement Algorithm with Composite Neighbourhood Structures for the

University Course Timetabling Problem, In Metaheuristics - Progress in Complex Systems Optimization (Doerner K. F., Gendreau M., Greistorfer P.,

Gutjahr W. J., Hartl R. F., and Reimann M., Eds.), Operations Research/Computer Science Interfaces 39, 153-169. Springer US, 2007.

Bacardit J., and Butz M. V., Data Mining in Learning Classifier Systems: Comparing XCS with GAssist In Learning Classifier Systems,

Revised Selected Papers of the International Workshop on Learning Classifier Systems 2003-2005 (Kovacs T., Llorà X., Takadama K.,

Lanzi P. L., Stolzmann W., Wilson S. W., Eds.), Lecture Notes in Artificial Intelligence 4399, 282-290. Springer-Verlag, 2007.

Bacardit J., and Garrell J. M., Bloat Control and Generalization Pressure Using The Minimum Description Length Principle for a Pittsburgh

approach Learning Classifier System, In Learning Classifier Systems, Revised Selected Papers of the International Workshop on Learning

Classifier Systems 2003-2005 (Kovacs T., Llorà X., Takadama K., Lanzi P. L., Stolzmann W., Wilson S. W., Eds.), Lecture Notes in Artificial

Intelligence 4399, 59-79. Springer-Verlag, 2007.

Bacardit J., Goldberg D. E., and Butz M. V., Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule,

In Learning Classifier Systems, Revised Selected Papers of the International Workshop on Learning Classifier Systems 2003-2005 (Kovacs T.,

Llorà X., Takadama K., Lanzi P. L., Stolzmann W., Wilson S. W., Eds.), Lecture Notes in Artificial Intelligence 4399, 291-307. Springer-Verlag, 2007.

Bargiela A., Travel Time Estimation Through Statistical Correlation Of Inductive Loop Readings, In Crisp and Fuzzy Essays on Transportation

Research (R. Tapio Luttinen, Ed.), 323-332, HUT Publications 110, Espoo, 2007.

Baxter J. L., Burke E. K., Garibaldi J. M., and Norman M., Multi-Robot Search and Rescue: A Potential Field Based Approach, In Autonomous

Robots and Agents (Mukhopadhyay S. and Sen Gupta G., Eds.), Studies in Computational Intelligence 76, 9-16. Springer Verlag, 2007.

Beyrouthy C., Burke E. K., Landa-Silva D., McCollum B., McMullan P., and Parkes A. J., The Teaching Space Allocation Problem with Splitting,

In Practice and Theory of Automated Timetabling VI: Revised Selected papers from the 6th international conference, PATAT, Aug 30-Sep 1,

2006 (Burke E. K. and Rudova H., Eds.), Lecture Notes in Computer Science 3867, 228-247. Springer-Verlag, Brno, Czech Republic, 2007.

Chong S. Y., Humble J., Kendall G., Li J. and Yao X., The Iterated Prisoners’ Dilemma: 20 Years On, In The Iterated Prisoners’ Dilemma:

20 Years On (Kendall G., Yao X. and Chong S. Y., Eds.), Advances in Natural Computation 4, Chapter 1, 1-21, World Scientific, Singapore, 2007.

Chong S. Y., Humble J., Kendall G., Li J. and Yao X., Iterated Prisoner’s Dilemma and Evolutionary Game Theory, In The Iterated Prisoners’ Dilemma:

20 Years On (Kendall G., Yao X. and Chong S. Y., Eds.), Advances in Natural Computation 4, Chapter 2, 23-62, World Scientific, Singapore, 2007.

Chong S. Y., Humble J., Kendall G., Li J. and Yao X., Learning IPD Strategies through Coevolution, In The Iterated Prisoners’ Dilemma: 20 Years On

(Kendall G., Yao X. and Chong S. Y., Eds.), Advances in Natural Computation 4, Chapter 3, 63-87, World Scientific, Singapore, 2007.

Li L., Siepmann P., Smaldon J., Terrazas G., and Krasnogor N., Automated Self-Assembling Programming, In Systems Self-Assembly:

Multi-Disciplinary Snapshops (Krasnogor N., Gustafson S., Pelta D. A., and Verdegay J. L., Eds.), Volume 5, 281-307. Elsevier, 2007.

28 A S A P

PhD Theses 2008Atkin J., On-line decision support for take-off runway scheduling at London Heathrow airport, PhD thesis, School of Computer Science

and Information Technology, University of Nottingham, 2008.

Barteczko-Hibbert C., An Artificial Neural Network Model for the Optimisation of Diverse Domestic Energy Systems, PhD thesis, School

of Computer Science and Information Technology, University of Nottingham, 2008.

Yaakob R., Integration of a Best Population Pool and Social Learning: An Investigation in Game Playing, PhD thesis, School of Computer

Science and Information Technology, University of Nottingham, 2008.

2007Spoerer K., The Lemmings Puzzle: Computational Complexity of an Approach and Identification of Difficult Instances, PhD thesis, School

of Computer Science and Information Technology, University of Nottingham, 2007.

Moss, B., The Data Integrity Problem and Multi-Layered Document Integrity, PhD thesis, School of Computer Science and Information

Technology, University of Nottingham, 2007.

Tadrus, S., Generic Multi-Pheromone Quality of Service Routing, PhD thesis, School of Computer Science and Information Technology,

University of Nottingham, 2007.

Wang X.-Y., Fuzzy Clustering in the Analysis of Fourier Transform Infrared Spectra for Cancer Diagnosis, PhD thesis, School of Computer

Science and Information Technology, University of Nottingham, 2007

Journal Papers in PressAgafonov E., Bargiela A., Burke E. and Peytchev E., Mathematical Justification of a Heuristic for Statistical Correlation of Real-Life Time

Series, accepted for publication in European Journal of Operational Research, to appear 2009.

Aickelin U., Burke E., and Li J., Improved Squeaky Wheel Optimisation for Robust Personnel Scheduling, accepted for publication in

IEEE Transactions on Evolutionary Computation, to appear 2009.

Alcalá-Fdez J., Sánchez L., García S., del Jesus M. J., Ventura S., Garrell J., Otera J., Romero C., Bacardit J., Rivas V., and Fernández J., KEEL:

A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems, accepted for publication in Soft Computing - A Fusion of

Foundations, Methodologies and Applications, to appear 2009.

Asmuni H., Burke E. K., Garibaldi J. M., McCollum B., and Parkes A. J., An Investigation of Fuzzy Multiple Heuristic Orderings in the

Construction of University Examination Timetables, accepted for publication in Computers and Operations Research, to appear 2009.

Bacardit J., Burke E., and Krasnogor N., Improving the Scalability of Rule-Based Evolutionary Learning, accepted for publication in

Memetic Computing, to appear 2009.

Bacardit J., and Krasnogor N., Performance and Efficiency of Memetic Pittsburgh Learning Classifier Systems, accepted for publication in

Evolutionary Computation, to appear 2009.


Beddoe G., Petrovic S., and Li J., A Hybrid Metaheuristic Case-based Reasoning System for Nurse Nostering, accepted for publication in

Journal of Scheduling, to appear 2009.

Beyrouthy C., Burke E. K., Landa-Silva J. D., McCollum B., McMullan P., and Parkes A. J., Towards Improving the Utilisation of University

Teaching Space, accepted for publication in Journal of the Operational Research Society, to appear 2009.

Burke E.K., Hellier R.S.R., Kendall G., and Whitwell G., Irregular Packing using the Line and Arc No-Fit Polygon, accepted for publication in

Operations Research, to appear 2009.

Burke E.K., Kendall G., and Whitwell G., A Simulated Annealing Enhancement of the Best-Fit Heuristic for the Orthogonal Stock Cutting

Problem, accepted for publication in INFORMS Journal on Computing, to appear 2009.

Huy N. Q., Soon O. Y., Hiot L. M., and Krasnogor N., Adaptive Cellular Memetic Algorithm, accepted for publication in Evolutionary Computation,

to appear 2009.

Li J., Aickelin U., and Burke E., A Component Based Heuristic Search Method with Evolutionary Eliminations for Hospital Personnel

Scheduling, accepted for publication in INFORMS Journal on Computing, to appear 2009.

Li J., Garibaldi J., and Krasnogor N., Automated Self-Assembly Programming Paradigm: The Impact of Network Topology, accepted for

publication in International Journal of Intelligent Systems, to appear 2009.

Li J., and Kendall G., A Strategy with Novel Evolutionary Features for the Iterated Prisoner’s Dilemma, accepted for publication in

Evolutionary Computation, to appear 2009.

McCollum B., McMullan P, Paechter B., Lewis R., Schaerf A., Di Gaspero L., Parkes A. J., Qu R., and Burke E., Setting the Research Agenda in

Automated Timetabling: The Second International Timetabling Competition, accepted for publication in INFORMS Journal of Computing, to

appear 2009.

Melville J. L., Burke E. K., and Hirst J. D., Machine Learning in Virtual Screening, accepted for publication in Combinatorial Chemistry &

High Throughput Screening, to appear 2009.

Özcan E., and Başaran C., A Case Study of Memetic Algorithms for Constraint Optimization, accepted for publication in

Soft Computing - A Fusion of Foundations, Methodologies and Applications, to appear 2009.

Ouelhadj D., and Petrovic S., Survey of Dynamic Scheduling in Manufacturing Systems, accepted for publication in Journal of Scheduling,

to appear 2009.

Qu R., Burke E., and McCollum B., Adaptive Automated Construction of Hybrid Heuristics for Exam Timetabling and Graph Colouring

Problems, accepted for publication in European Journal of Operational Research, to appear 2009.

Qu R., Burke E., McCollum B., Merlot L., and Lee S., A Survey of Search Methodologies and Automated System Development for

Examination Timetabling, accepted for publication in Journal of Scheduling, to appear 2009.

Stout M., Bacardit J., Hirst J., Smith R., and Krasnogor N., Prediction of Topological Contacts in Proteins Using Learning Classifier Systems,

accepted for publication in Soft Computing - A Fusion of Foundations, Methodologies and Applications, to appear 2009.

30 A S A P

Xiao K., Ho S.H., and Bargiela A., Brain MRI Tumor Segmentation with the Assistance of Lateral Ventricular Deformation Estimation, accepted

for publication in Journal of Australasian College of Physical Scientists and Engineers in Medicine, to appear 2009.

Journal Papers 2008Atkin J., E.K.Burke , Greenwood J., and Reeson D., On-line Decision Support for Take-off Runway Scheduling with Uncertain Taxi Times at

London Heathrow Airport, Journal of Scheduling, 11(5):323-346, 2008.

Ayob M., and Kendall G., A Survey of Surface Mount Device Placement Machine Optimisation: Machine Classification, European Journal of

Operational Research, 186(3):893-914, 2008.

Bai R., and Kendall G., A Model for Fresh Produce Shelf Space Allocation and Inventory Management with Freshness Condition Dependent

Demand, INFORMS Journal on Computing, 20(1):78-85, 2008.

Bai R., Burke E. K., and Kendall G., Heuristic, Meta-Heuristic and Hyper-Heuristic Approaches for Fresh Produce Inventory Control and Shelf

Space Allocation, Journal of the Operational Research Society, 59(10): 1387-1397, 2008.

Bargiela A., and Pedrycz W., Toward a Theory Of Granular Computing for Human-Centred Information Processing, IEEE Trans. on Fuzzy

Systems, vol. 16, 2, 320-330, 2008.

Binner J.M., Gazely A.M., and Kendall G., Evaluating the Performance of a EuroDivisia Index Using Artifcial Intelligence Techniques,

International Journal of Automation and Computing, 5(1):58-62, 2008.

Burke E. K., Curtois T. E., Post G., Qu R., and Veltman B., A Hybrid Heuristic Ordering and Variable Neighbourhood Search for the Nurse

Rostering Problem, European Journal of Operational Research, 188:330-341, 2008.

Burke E. K., Dror M., and Orlin J., Scheduling Malleable Tasks with Interdependent Processing Rates: Comments and Observations,

Discrete Applied Mathematics, 156(5):620-626, 2008.

Chong S. Y., Tino P., and Yao X., Measuring Generalization Performance in Co-evolutionary Learning, IEEE Transactions on Evolutionary

Computation, 12(4):479-505, 2008.

Gheorghe M., Krasnogor N., and Camara M., P Systems Applications to Systems Biology, Biosystems, 91:435-437, 2008.

Kendall G., Scheduling English Football Fixtures Over Holiday Periods, Journal of the Operational Research Society, 59(6):743-755, 2008.

Kendall G., Parkes A. J., and Spoerer K., A Survey of NP-Complete Puzzles, International Computer Games Association Journal, 31(1):13-34, 2008.

Krasnogor N. and Smith J., Memetic Algorithms: The Polynomial Local Search Complexity Theory Perspective, Journal of Mathematical

Modelling and Algorithms, 7:3-24, 2008.

Oakley M. T., Barthel D., Bykov Y., Garibaldi J. M., Burke E. K., Krasnogor N., and Hirst J. D., Search strategies in structural bioinformatics,

Current Protein and Peptide Science, Bentham Science Publishers, 9(3):260-274, 2008.


Oates R., Kendall G., and Garibaldi J. M., Frequency Analysis for Dendritic Cell Population Tuning: Decimating the Dendritic Cell,

Evolutionary Intelligence, 1(2):145-157, 2008.

Petrovic S., Fayad C., and Petrovic D., Sensitivity Analysis of a Fuzzy Multiobjective Scheduling Problem, International Journal of

Production Research, 46(12):3327-3344, 2008.

Petrovic S., Fayad C., Petrovic D., Burke E., and Kendall G., Fuzzy Job Shop Scheduling with Lot-sizing, Annals of Operations Research,

159(1):275-292, 2008.

Shah A. A., Barthel D., Lukasiak P., Blazewicz J., and Krasnogor N., Web & Grid technologies in Bioinformatics, Computational and Systems

Biology: A Review, Current Bioinformatics, 3:10-31, 2008.

Stout M., Bacardit J., Hirst J., and Krasnogor N., Prediction of Recursive Convex Hull Class Assignments for Protein Residues, Bioinformatics,

24(7):916-923, 2008.

Tomassini M., Verel S., and Ochoa G., Complex Networks Analysis of Combinatorial Spaces: The NK Landscape Case, Physical Review E,

78(6):66114 - 66123, 2008.

Wang W., Barnaghi P. and Bargiela A., Search with Meanings: An Overview of Semantic Search Systems, Int. J. Communications of SIWN,

3, 76-82, 2008.

2007Abdullah S., Ahmadi S., Burke E., and Dror M., Investigating Ahuja-Orlin’s Large Neighbourhood Search Approach for Examination

Timetabling, OR Spectrum, 29(2):351-372, 2007.

Abdullah S., Ahmadi S., Burke E. K., Dror M., and McCollum B., A Tabu Based Large Neighbourhood Search Methodology for the Capacitated

Examination Timetabling Problem, Journal of the Operational Research Society, 58(11):1494-1502, 2007.

Aickelin U., Burke E. K., and Li J., An Estimation of Distribution Algorithm with Intelligent Local Search for Rule-based Nurse Rostering,

Journal of the Operational Research Society, 58(12):1574-1585, 2007.

Aickelin U., and Li J., An Estimation of Distribution Algorithm for Nurse Scheduling, Annals of Operations Research, 155(1):289-309, 2007.

Atkin J. A., Burke E. K., Greenwood J., and Reeson D., Hybrid Meta-heuristics to Aid Runway Scheduling at London Heathrow Airport,

Transportation Science, 41(1):90-106, 2007.

Bargiela A., and Pedrycz W., Toward a Theory of Granular Computing for Human-Centered Information Processing, IEEE Transactions On

Fuzzy Systems, 16(2):320-330, 2007.

Bargiela A., Pedrycz W., and Nakashima T., Multiple Regression with Fuzzy Data, Fuzzy Sets and Systems, 158:2169-2188, 2007.

Barthel D., Hirst J., Blazewicz J., Burke E., and Krasnogor N., Procksi: A Decision Support System For Protein (Structure) Comparison,

Knowledge, Similarity and Information, BMC Bioinformatics, 8:416, 2007.

Beddoe G., and Petrovic S., Enhancing Case-based Reasoning For Personnel Rostering With Selected Tabu Search Concepts,

Journal of the Operational Research Society, 58(12):1586-1598, 2007.

32 A S A P

Bernardini F., Gheorghe M., and Krasnogor. N., Quorum sensing P systems, Theoretical Computer Science, 371(1-2):20-33, 2007.

Blazewicz J., Burke E. K., Kazprzak M., Kovyalov A., and Kovyalov M. Y., The Simplified Partial Digest Problem: Enumerative and Dynamic

Programming Algorithms, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 4(4):668-680, 2007.

Burke E. K., Hellier R. S. R., Kendall G., and Whitwell G., Complete and Robust No-Fit Polygon Generation for the Irregular Stock Cutting

Problem, European Journal of Operational Research, 179(1):27-49, 2007.

Burke E. K., McCollum B., Meisels A., Petrovic S., and Qu R., A Graph-Based Hyper-Heuristic for Educational Timetabling Problems,

European Journal of Operational Research, 176:177-192, 2007.

Chong S. Y., and Yao X., Multiple Choices and Reputation in Multiagent Interactions, IEEE Transactions on Evolutionary Computation,

11(6):689-711, 2007.

Dowsland K., Gilbert M., and Kendall G., A Local Search Approach to a Circle Cutting Problem Arising in the Motor Cycle Industry, Journal of

the Operational Research Society, vol. 58, 429-438, 2007.

Dowsland K. A., Soubeiga E., and Burke E. K., A Simulated Annealing Hyper-Heuristic for Determining Shipper Sizes,

European Journal of Operational Research, 179(3):759-774, 2007.

Jaskowski W., Blazewicz J., Lukasiak P., Milostan M., and Krasnogor N., 3D-Judge - A Metaserver Approach to Protein Structure Prediction,

Foundations of Computing and Decision Sciences, 31(1), 2007.

Kendall G., and Su Y., Imperfect Evolutionary Systems, IEEE Transactions on Evolutionary Computation, 1(3):294-307, 2007.

Landa-Silva J. D., and Burke E. K., Asynchronous Cooperative Local Search for the Office Space Allocation Problem,

INFORMS Journal on Computing, 19(4):575-587, 2007.

Ochoa G., Villasana M., and Burke E. K., An Evolutionary Approach to Cancer Chemotherapy Scheduling,

Genetic Programming and Evolvable Machines, 8(4):301-318, 2007.

Ong Y., Krasnogor N., and Ishibuchi H., Special Issue on Memetic Algorithms, IEEE Transactions on Systems, Man and Cybernetics, Part B,

37(1):2-5, 2007.

Petrovic D., Duenas A., and Petrovic S., Decision Support Tool for Multi-Objective Job Shop Scheduling Problems with Linguistically

Quantified Decision Functions, Decision Support Systems, 43(4):1527-1538, 2007.

Petrovic S., Yang Y., and Dror M., Case-Based Selection of Initialisation Heuristics for Metaheuristic Examination Timetabling,

Expert Systems with Applications, 33(3):772-785, 2007.

Siepmann P., Martin C., Vancea I., Moriarty P., and Krasnogor N., A Genetic Algorithm Approach to Probing the Evolution of Self-Organised

Nanostructured Systems, Nano Letters, 7(7):1985-1990, 2007.

Terrazas G., Siepmann P., Kendall G., and Krasnogor N., An Evolutionary Methodology for the Automated Design of Cellular Automaton-

based Complex Systems, Journal of Cellular Automata, 2:77-102, 2007.

The ASAP group also published many peer reviewed conference papers from 2007-2008. Please refer to the following page to view the full list:

http://www�asap�cs�nott�ac�uk/newpublications/twiki/bin/view/ASAP/ConferencePapers/


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t

Co-i

nves

tigat

or(s

)Fu

ndin

g B

ody

Colla

bora

tor(

s)D

ates

Tota

l A

mou

ntN

otes

Han

dlin

g U

ncer

tain

ties

in

Tran

spor

tatio

n an

d Lo

gist

ics

Usi

ng

Gra

nula

r Com

putin

g an

d H

yper

-

heur

istic

s

Bai

Qu,

Bur

ke,

Bar

giel

a

Nin

gbo

Mun

icip

al

Scie

nce

and

Tech

nolo

gy

Bur

eau,

Chi

na

1/

9/20

08

to 3

1/12

/201

1

£10,

000

This

is a

pro

ject

aw

arde

d to

the

Uni

vers

ity o

f N

ottin

gham

Nin

gbo,

Chi

na, f

unde

d by

Chi

na N

ingb

o M

unic

ipal

Nat

ural

Scie

nce

Foun

datio

n

An

Inve

stig

atio

n of

the

Rob

ustn

ess

of T

rans

port

atio

n Sc

hedu

ling

for

Mod

ern

Logi

stic

s.

Bai

Bar

giel

a,

Anb

erre

e

Nin

gbo

Mun

icip

al

Nat

ural

Sci

ence

Foun

datio

n,

Chin

a

1/

2/20

08

to 2

8/2/

2010

50,0

00

RM

B

(£4,

500)

This

is a

pro

ject

aw

arde

d to

the

Uni

vers

ity o

f N

ottin

gham

Nin

gbo,

Chi

na, f

unde

d by

Chi

na N

ingb

o M

unic

ipal

Nat

ural

Scie

nce

Foun

datio

n

Hum

an-c

entr

ed In

form

atio

n

Proc

essi

ng T

hrou

gh G

ranu

lar

Mod

ellin

g

Bar

giel

aPe

dryc

zEP

SRC

(EP/

C512

74X/

2)

£122

80

1/9/

2007

31/7

/200

8

£12,

280

This

pro

ject

is a

con

tinua

tion

of (

EP/C

5127

4X/1

)

The

LAN

CS (

Lanc

aste

r, N

ottin

gham

,

Card

iff a

nd S

outh

ampt

on)

Initi

ativ

e

in F

ound

atio

nal O

pera

tiona

l

Res

earc

h: B

uild

ing

Theo

ry fo

r

Prac

tice

Bur

keEP

SRC

S&I A

war

d

(EP/

F033

214/

1)

Lanc

aste

r, Ca

rdiff

and

Sout

ham

pton

Uni

vers

ities

01/0

9/08

to 3

1/8/

2014

£1,9

88,9

20Th

is m

ajor

EPS

RC

awar

d is

par

t of

a £

12M

+ in

itiat

ive

invo

lvin

g

thre

e ot

her u

nive

rsiti

es (

Lanc

aste

r, Ca

rdiff

and

Sou

tham

pton

).

The

initi

ativ

e ai

ms

to b

uild

nat

iona

l cap

acity

in O

pera

tiona

l

Res

earc

h an

d to

clo

se t

he g

ap b

etw

een

theo

retic

al O

R a

nd

indu

stria

l pra

ctic

e. T

he c

onso

rtiu

m h

as re

ceiv

ed o

ver £

5.4M

in

tota

l fro

m E

PSR

C an

d th

e in

stitu

tions

hav

e co

ntrib

uted

ove

r £7M

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Not

tingh

am’s

cont

ribut

ion

is o

ver £

2.4M

Nex

t G

ener

atio

n D

ecis

ion

Supp

ort:

Aut

omat

ing

the

Heu

ristic

Des

ign

Proc

ess

Bur

keLa

nda

Silv

a,

Petr

ovic

,

Kend

all,

Gar

ibal

di,

Kra

snog

or, Q

u

EPSR

C

(EP/

D06

1571

/1)

£2,6

63,5

28

1/

10/2

006

to 3

0/9/

2011

£2,6

63,5

28Th

is is

a m

ajor

initi

ativ

e to

exp

lore

how

deci

sion

sup

port

sys

tem

s ca

n de

sign

sea

rch

met

hodo

logi

es

PLAT

FOR

M: T

owar

ds M

ore

Gen

eral

Opt

imis

atio

n/Se

arch

Sys

tem

s

Bur

keKe

ndal

l

Gar

ibal

di

Petr

ovic

Kra

snog

or

EPSR

C

(GR

/S70

197/

01)

£422

,908

1/

2/20

04

to 3

1/1/

2009

£422

,908

This

is a

pre

stig

ious

EPS

RC

Plat

form

aw

ard

An

Inve

stig

atio

n of

the

role

of

Gen

etic

Prog

ram

min

g in

a H

yper

-heu

ristic

Fram

ewor

k

Bur

keKe

ndal

l

Kra

snog

or

EPSR

C

(EP/

C523

385/

1)

£227

,675

BTG

plc

£15,

000

1/10

/200

5

to 3

0/9/

2008

£242

,675

This

is a

col

labo

rativ

e pr

ojec

t w

ith t

he U

nive

rsity

of

Esse

x

Ada

ptiv

e M

ulti-

Obj

ectiv

e H

euris

tic

and

Met

a-he

uris

tic A

ppro

ache

s to

Spac

e A

lloca

tion

Bur

keKe

ndal

l

Land

a Si

lva

EPSR

C

(GR

/T26

115/

01)

£205

,378

Rea

l Tim

e So

lutio

ns L

td

£112

,500

8/4/

2005

to 7

/4/2

009

£317

,878

This

is f

unde

d un

der E

PSR

C’s

Mat

hem

atic

s fo

r Bus

ines

s in

itiat

ive

Gra

nts

Title

Prin

cipa

l Inv

estig

ator

/

Lead

Sci

entis

t

Co-i

nves

tigat

or(s

)Fu

ndin

g B

ody

Colla

bora

tor(

s)D

ates

Tota

l A

mou

ntN

otes

Nov

el M

etah

euris

tics

Res

earc

h

Dire

ctio

ns in

Hea

lthca

re P

erso

nnel

Ros

terin

g

Bur

kePe

trov

ic

Kend

all

EPSR

C

(GR

/S31

150/

01)

£191

,581

ORT

EC C

onsu

ltant

s BV

,

Gow

er

Opt

imal

Alg

orith

ms

Ltd,

KaH

o

St.-

Liev

en £

106,

500

1/10

/200

3

to 3

1/3/

2007

£298

,081

This

pro

ject

aim

s to

cut

acr

oss

the

disc

iplin

ary

boun

darie

s of

Ope

ratio

nal R

esea

rch

and

Art

ifici

al In

telli

genc

e an

d ca

rry

out

an

inno

vativ

e an

d tim

ely

rese

arch

initi

ativ

e in

hea

lthca

re p

erso

nnel

rost

erin

g

Hyb

rid M

etah

euris

tics

App

roac

hes

for A

ir Tr

affic

Con

trol

Sch

edul

ing

Bur

ke

EPSR

C

(Sm

ith In

st)

£40,

000

NAT

S Lt

d

(for

mer

ly N

atio

nal A

ir

Traf

fic S

ervi

ces

Ltd)

£21,

000

1/10

/200

3

to 3

0/9/

2006

£61,

000

This

is a

n EP

SRC

CASE

stu

dent

ship

thr

ough

the

Sm

ith In

stitu

te

for S

yste

ms

Engi

neer

ing

and

Indu

stria

l Mat

hem

atic

s

Mod

els

and

Alg

orith

ms

for C

ompl

ex

Sche

dulin

g Pr

oble

ms:

A V

isiti

ng

Fello

wsh

ip

Bur

keG

arib

aldi

EPSR

C

(GR

/T23

374/

01)

£21,

240

1/

10/2

004

to 3

0/9/

2009

£21,

240

This

pro

ject

sup

port

s a

visi

ting

fello

wsh

ip fo

r Pro

f. Pe

ter B

ruck

er,

Osn

abru

ck

DN

A M

appi

ng b

y Co

mbi

nato

rial

Opt

imis

atio

n -

A V

isiti

ng F

ello

wsh

ip

Bur

keKe

ndal

l

Kra

snog

or

EPSR

C

(GR

/S64

530/

01)

£10,

224

1/

9/20

03

to 3

1/5/

2007

£10,

224

This

pro

ject

sup

port

s a

visi

ting

fello

wsh

ip fo

r Pro

f. Ja

cek

Bla

zew

icz,

Poz

nan

Inve

stig

atin

g A

utom

ated

Met

hodo

logi

es t

o G

ener

ate

the

Targ

et S

tart

-up

App

rova

l Tim

e at

Lond

on H

eath

row

Bur

ke

N

ATS

Ltd

(for

mer

ly N

atio

nal A

ir

Traf

fic S

ervi

ces

Ltd)

£37,

800

1/4/

2007

to 1

/1/2

009

£37,

800

This

is a

n in

vest

igat

ion

with

Nat

iona

l Air

Traf

fic S

ervi

ces

Ltd

into

how

aut

omat

ed d

ecis

ion

supp

ort

coul

d ai

d co

ntro

llers

at

Hea

thro

w w

ith t

he s

tart

-up

appr

oval

tim

e al

loca

tion

in a

dvan

ce.

Opt

imis

atio

n M

etho

ds in

Hea

lth C

are

Plan

ning

Bur

keR

esea

rch

Coun

cil

of N

orw

ay

SIN

TEF

1/10

/200

7

to 3

0/9/

2012

NO

K

625,

000

(£63

,485

)

This

is a

col

labo

rativ

e pr

ojec

t w

ith S

INTE

F, in

Nor

way

. The

who

le

cons

ortiu

m re

ceiv

ed N

OK

9,3

75,0

00.

BIO

PTR

AIN

- R

esea

rch

Trai

ning

Net

wor

k fo

r Bio

info

rmat

ics

Opt

imis

atio

n

Gar

ibal

diB

urke

Kra

snog

or

EU

(FP6

-IST

-007

597)

£537

,359

1/

9/20

05

to 3

1/8/

2009

£537

,359

This

is a

col

labo

rativ

e pr

ojec

t w

ith 4

oth

er E

urop

ean

inst

itutio

ns

to s

uppo

rt 1

2 Ph

D s

tude

nts,

wor

th a

tot

al o

f ov

er £

2M a

cros

s th

e

cons

ortiu

m

SRIF

2: In

fras

truc

ture

for

Colla

bora

tive

Dec

isio

n M

akin

g in

Unc

erta

in E

nviro

nmen

ts

Gar

ibal

diB

urke

Kend

all

SRIF

2

(SR

IF2)

£280

,000

Mer

lin S

yste

ms

Corp

Ltd

£140

,000

1/10

/200

4

to 3

0/9/

2008

£420

,000

This

pro

ject

is a

par

t of

a la

rger

aw

ard

for U

biqu

itous

eSc

ienc

e

and

Grid

Infr

astr

uctu

re w

orth

a t

otal

of

£2.3

M

BIO

PATT

ERN

- C

ompu

tatio

nal

Inte

llige

nce

for B

iopa

tter

n A

naly

sis

in S

uppo

rt o

f e-

heal

thca

re

Gar

ibal

diB

urke

Kra

snog

or

EU

(IST

e-h

ealth

5088

03)

£221

,623

1/

1/20

04

to 3

1/12

/200

7

£221

,623

This

is a

col

labo

rativ

e pr

ojec

t w

ith t

he S

choo

l of

Chem

istr

y. A

Fram

ewor

k 6

Net

wor

k of

Exc

elle

nce

was

aw

arde

d £6

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to

a

cons

ortiu

m o

f 31

par

tner

s

Tow

ards

a F

ram

ewor

k fo

r Mod

ellin

g

Varia

tion

in A

utom

ated

Dec

isio

n

Supp

ort

Gar

ibal

diB

urke

EPSR

C

(EP/

C542

207/

1)

£143

,282

1/

7/20

06

to 3

0/6/

2009

£143

,282

This

is a

col

labo

rativ

e pr

ojec

t w

ith D

e M

ontf

ort

Uni

vers

ity

Title

Prin

cipa

l Inv

estig

ator

/

Lead

Sci

entis

t

Co-i

nves

tigat

or(s

)Fu

ndin

g B

ody

Colla

bora

tor(

s)D

ates

Tota

l A

mou

ntN

otes

Serv

ice

Leve

l Agr

eem

ent

Bas

ed

Sche

dulin

g H

euris

tics

Gar

ibal

diB

urke

Petr

ovic

EPSR

C

(GR

/S67

661/

01)

£141

,492

1/

2/20

04

to 3

1/10

/200

7

£141

,492

This

is f

unde

d un

der t

he F

unda

men

tal C

ompu

ter S

cien

ce fo

r

e-Sc

ienc

e ca

ll. It

is a

col

labo

rativ

e pr

ojec

t w

ith t

he U

nive

rsity

of

Man

ches

ter

Colla

bora

tive

Dec

isio

n M

akin

g in

Unc

erta

in E

nviro

nmen

ts

Gar

ibal

diB

urke

EPSR

C

(Sm

ith In

st)

£40,

000

Mer

lin S

yste

ms

Corp

Ltd

£27,

000

1/10

/200

4

to 3

0/9/

2007

£67,

000

This

is a

n EP

SRC

CASE

stu

dent

ship

thr

ough

the

Sm

ith In

stitu

te

for S

yste

ms

Engi

neer

ing

and

Indu

stria

l Mat

hem

atic

s

Hyp

er-h

euris

tics

for S

ched

ulin

g,

Ros

terin

g an

d R

outin

g: A

n

Inte

rnat

iona

l Col

labo

ratio

n

Gar

ibal

diB

urke

Kend

all

EPSR

C

(EP/

D02

7039

/1)

£31,

828

26

/5/2

006

to 2

5/5/

2011

£31,

828

This

sup

port

s a

visi

ting

fello

wsh

ip fo

r Pro

f M

iche

l Gen

drea

u,

Mon

trea

l

A N

atio

nal T

augh

t Co

urse

Cen

tre

in

Ope

ratio

nal R

esea

rch

(NAT

COR

)

Gla

zebr

ook

Bur

keEP

SRC

(EP/

E502

067/

1)

£241

,052

1/

10/2

006

to 3

0/9/

2011

£241

,052

This

is a

UK-

wid

e in

itiat

ive

to p

rovi

de a

hig

h le

vel o

f ta

ught

cour

se P

hD p

rovi

sion

. It

invo

lves

Lan

cast

er, N

ottin

gham

,

Sout

ham

pton

, Car

diff

, Bru

nel a

nd W

arw

ick

Hyb

rid M

eta-

heur

istic

Opt

imis

atio

n

of C

hira

l Cat

alys

ts

Hirs

tB

urke

EPSR

C

(GR

/S75

765/

01)

£220

,227

1/

4/20

04

to 3

0/9/

2007

£220

,227

This

is a

col

labo

rativ

e pr

ojec

t w

ith t

he S

choo

l of

Chem

istr

y

Cent

re fo

r Pla

nt In

tegr

ativ

e B

iolo

gy:

Nov

el M

odel

ling

Para

digm

s

Hod

gman

Kra

snog

orB

BSR

C

(BB

/D01

9613

/1)

£500

,768

1/

2/20

07

to 3

1/1/

2012

£500

,768

This

is p

art

of t

he £

9.2M

Cen

tre

for P

lant

Inte

grat

ive

Bio

logy

An

Inve

stig

atio

n of

Cut

ting/

Pack

ing

and

Plan

ning

usi

ng A

utom

ated

Alg

orith

m S

elec

tion

Kend

all

Bur

keEP

SRC

(GR

/S52

414/

01)

£153

,670

2/

2/20

04

to 1

/2/2

007

£153

,670

This

is a

col

labo

rativ

e pr

ojec

t w

ith t

he U

nive

rsity

of

Sout

ham

pton

An

Inve

stig

atio

n of

Col

labo

rativ

e

Rob

otic

s

Kend

all

activ

med

ia

£20,

965

1/3/

2006

to 2

8/2/

2009

£20,

965

This

pro

ject

pro

vide

s in

dust

rial s

uppo

rt fo

r a U

nive

rsity

of

Not

tingh

am f

unde

d CA

SE s

tude

ntsh

ip

EP/E

0179

75/1

: An

Inve

stig

atio

n

of R

egul

ator

y D

ecis

ion

Mak

ing

by

Aut

omat

ed D

ecis

ion

Mak

ers

Kend

all

Polla

rd

Soan

e

EPSR

C

(EP/

E017

975/

1)

£222

,411

Dep

t fo

r Env

Foo

d an

d

Rur

al A

ffai

r

1/10

/200

6

to 3

1/10

/200

9

£222

,411

This

is a

n EP

SRC

Idea

s Fa

ctor

y Pr

ojec

t

EP/D

0310

79/1

: NET

WO

RK

:

Inte

rdis

cipl

inar

y Cu

ttin

g, P

acki

ng

and

Spac

e A

lloca

tion

Kend

all

Bur

keEP

SRC

Apt

ia S

olut

ions

Ltd,

Gow

er O

ptim

al

Alg

orith

ms

Ltd,

JoT

IKa

(Mid

land

s) S

oftw

are

Ltd,

Real

Tim

e So

lutio

ns L

td,

Sigm

aTEK

Eur

ope

Ltd

1/3/

2006

to 2

8/02

/200

9

£63,

212

This

is a

n EP

SRC

NET

WO

RK

(Sem

i) Fo

rmal

Art

ifici

al L

ife T

hrou

gh

P-sy

stem

s &

Lea

rnin

g Cl

assi

fier

Syst

ems:

An

Inve

stig

atio

n in

to

Info

Bio

tics

Kra

snog

orCa

mar

a

Will

iam

s

EPSR

C

(EP/

E017

215/

1)

£515

,565

Colla

bora

ting

with

the

Cent

re F

or B

iom

olec

ular

Scie

nces

, UoN

1/9/

2007

to 3

1/8/

2010

£515

,565

This

pro

ject

inve

stig

ates

a n

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sem

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8)

ASAP PersonnelAcademic Staff

Prof Edmund K� Burke

Head of Group Professor of Computer Science

(0115) 95 14206 [email protected] www.cs.nott.ac.uk/~ekb/

Dr Dario Landa-Silva

Lecturer

(0115) 84 66522 [email protected] www.cs.nott.ac.uk/~jds/

Prof Graham Kendall

Deputy Head of Group Dunford Professor of Computer Science

(0115) 84 66514 [email protected] www.cs.nott.ac.uk/~gxk/

Dr Ender Özcan

Science and Innovation Lecturer

(0115) 84 66569 [email protected] www.cs.nott.ac.uk/~exo/

Dr Jaume Bacardit

Lecturer

(0115) 84 67044 [email protected] www.cs.nott.ac.uk/~jqb/

Dr Andrew Parkes

Science and Innovation Lecturer

Room: B81 (0115) 95 14210 [email protected] www.cs.nott.ac.uk/~ajp/

Dr Ruibin Bai (UNMC)

Lecturer

Ningbo Campus, China +86 574 8818 0278 [email protected] www.cs.nott.ac.uk/~rzb/

Prof Sanja Petrovic

Professor of Computer Science

Room: C83 (0115) 95 14222 [email protected] www.cs.nott.ac.uk/~sxp/

Prof Andrzej Bargiela (UNMC)

Professor of Computer Science (UNMC)

(0115) 84 67279 [email protected] www.cs.nott.ac.uk/~abb/

Dr Rong Qu

Lecturer

Room: C43 (0115) 84 66503 [email protected] www.cs.nott.ac.uk/~rxq/

Dr Natalio Krasnogor

Associate Professor

(0115) 84 67592 [email protected] www.cs.nott.ac.uk/~nxk/

Dr Siang Yew Chong (UNMC)

Lecturer

Malaysia Campus +6 03 8924 8148 [email protected] baggins.nottingham.edu.my/~khczcsy/

38 A S A P

Administrative Staff

Debbie Pitchfork

ASAP Research Group Project Manager

(0115) 84 66543 [email protected]

Nick Poxon

ASAP Research Support Coordinator


Ebru Tasci

Administrative Assistant


Dr Gabriela OchoaDr Jason Atkin

Senior Research Fellows


Dr Yuri Bykov

Rupa Jagannathan

Dr German Terrazas Angulo

Dr HongQing Cao

Dr Hui Li

Dr Jamie Twycross

Dr Tim Curtois

Dr Jingpeng Li

Dr Antonio Vazquez

Dr Geert De Maere

Dr Jiawei Li

Dr Glenn Whitwell

Dr Matthew Hyde

Dr Djamila Ouelhadj

Research Associates

ASAP Personnel (continued)

40 A S A P

Sam Allen Belal Ismail Khalil Al-Khateeb

Zalilah Abd Aziz Monica Banerjea Jonathan Blakes

Pilar Camano Sobrino

Elkin Castro Juan Pedro Castro Gutierrez

Qun Bo Chen Jack Chaplin

Ha Duong Maria Franco Enrico Glaab Sven Groenemeyer Qiang Guo

Nor Hayati Hamid

Fang He Rob Hellier Joe Henry Obit Ebrahim Kamrani

Mohd Nizam Mohmad Kahar

Khoi Le Rahul Singh Majhail

Jakub Marecek Nishikant Mishra

PhD Students


Abdullah Muhammed

Patrick Barbosa Moratori

Robert Oates Tiago Pais Nam Pham

Syariza Abdul Rahman

Pedro Rocha Shamsudin MD Sarif

Peter Siepmann James Smaldon

Amr Soghier Mike Stout Adam Sweetman Azhar Ali Shah Syed

Özgür Ülker

Pawel WideraNadarajen Veerapen

Ying Xu

PhD Students

42 A S A P

See www.nottingham.ac.uk/ComputerScience/About/FindingUs.aspx/ for directions

Jacek Blazewicz

Peter Brucker Frederico Cruz Kathryn Dowsland Michel Gendreau

Jonathan Hirst

Barry McCollum

Thomas Runarsson

Müjgan Sağir Minaya Villasana

John Woodward

Visiting Fellows/Associated Staff

How to find us


Designed and printed by Eden Design and Creation www.edendesignandcreation.com

Editors: Prof Graham Kendall and Dr Ender Özcan

Automated Scheduling, Optimisation and Planning (ASAP) Research Group School of Computer Science The University of Nottingham Jubilee Campus, Wollaton Road Nottingham, NG8 1BB United Kingdom

http://www.asap.ac.uk/

© ASAP 2009

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