A simulation-optimization-based decision support system for water allocation
Simulation for Decision Support
Transcript of Simulation for Decision Support
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Simulation for Decision Support within the
Intelligent Modelling an Analysis Research Group
Version 17/02/2016
Peer-Olaf Siebers
UoN CompSci
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IMA: Intelligent Modelling and Analysis
• IMA is part of the School of Computer Science – 8 academic staff; 6 research fellows; 32 PhD students
– £5m as Principal Investigators + £25m as Co-Investigators
• Mission – Intelligently analyse and model complex data
– Creating new techniques (e.g. in data mining)
– Novel methods of addressing real-world problems
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IMA: Intelligent Modelling and Analysis
• Strong links to the Advanced Data Analysis Centre – Linking IMA research outputs to real-world applications
• Strong links to newly appointed data science professors – Thomas Gärtner
– Natasa Milic Frayling
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IMA: Intelligent Modelling and Analysis
• Quantitative research methods – AI-based Data Mining
– Evolutionary and other Bio-Inspired Algorithms
– Computational Modelling of Complex Systems
– Discrete and Agent-Based Simulation
– Multi-Criteria Decision Analysis
– Fuzzy Methodologies
– Medical Image Analysis
– Multi-Sensor Data Fusion
• Qualitative research methods – Structured Interviews
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Simulation Modelling Framework
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It's all about Agents and Agent-Based Modelling
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Research Interests
• Technical Aspects – From archetypes to multi-agent systems
– Engineering agent-based social simulations
• Using UML to define agents and their interactions
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From Archetypes …
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…
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… to Multi-Agent Systems
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Research Interest
• Applications – My Mission: Applying ABM to as many fields as possible
• Business studies (Risk Assessment; CBA; MCDA)
• Economics (Game Theory; Agent Based Computational Economics)
• Social Sciences (Political Science; Social Simulation)
• Engineering (Manufacturing; Urban Modelling; Energy; Transportation)
• Computer Science (Robotics; Game Development)
• Systems Biology
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Research Funding
• COI in "Future Energy Decision Making for Cities: Can Complexity Science Rise to the Challenge?"; EPSRC EP/G05956X/1 (£263,879); related to EPSRC EP/G059780/1
• PI in Test Driven Object Oriented Simulation Modelling; funded internally (£1,500)
• COI in Sustaining Urban Habitats: An Interdisciplinary Approach; Leverhulme RP2013-SL-015 (£1,750,000 x 2)
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Research Funding
• COI in Agent-Based Modelling for Simulating Peacebuilding: A Feasibility Study; funded internally by CompSci (£5,100)
• PI in Creating an Artificial Hotspot Laboratory Prototype for Investigating HGV Hotspot Incidences; funded internally by D^3 RPA Discipline Bridging Fund + ADAC (£11,200)
For more details see http://www.cs.nott.ac.uk/~pszps/research.html
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My Research Projects
• The Impact of Human Performance Variation on the Accuracy of Manufacturing System Simulation Models
• A Multi-Agent Simulation of Retail Management Practices
• Modelling and Analysing the Cargo Screening Process
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My Research Students
• Main supervisor – Sudhir Venkatesan: Comparative study of different analytical
paradigms for the evidence on antiviral treatment effectiveness for A(H1N1) pandemic influenza
– Olusola Theopilus: Exploring the usefulness of ABM/S to simulate and stimulate modal shift from road to rail
– Tuong Vu: A Software Engineering Approach for Agent-Based Modelling of Public Goods Game
– Mazlina Abdul Majid: Human Behaviour Modelling: An Investigation Using Traditional Discrete Event And Combined Discrete Event and Agent-Based Simulation
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My Research Students
• Additional supervisor – Tim Whiteley: Integrated whole system modelling and optimisation of
city resource flows
– Kunpeng Wang: Multi-scale model integration for the large-scale analysis of complex urban energy system
– James Burnett: What can user data relating to proximity and orientation tell us about real-world vs. simulation for interactive content delivery
– Felix Osebor: Sustainable urban mobility: A modelling framework for cities in rapidly developing countries
– Xia Li: Port operation evaluation with simulation and fuzzy based multi-stakeholder multi-criteria decision analysis
– Jacob Chapman: Multi-agent stochastic simulation of occupants' comfort and behaviour
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Outstanding Dissertation Students
• BSc and MSc students – Lim Zhi En: Using a Hybrid Approach on Climate Assessment
Modelling: Development of the HCAM Decision Support Tool
– Kukuh Nasrul Wicaksono: Study on Human Oriented System Simulation: Comparison of Different Methods to Represent Human Behaviour
– Adam Perkins: Modelling and Simulation of Rail Passengers to Evaluate Methods to Reduce Dwell Times
– Leanne May: Using Simulation to Assist Recruitment in Seasonally Dependant Contact Centers
– Olusola Faboya: On the Search for Novel Simulation Applications to Support Airport Operations Management
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Case Studies
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Department Store Customer Service
• Case study sector – Retail (department store operations)
• Developing some tools for understanding the impact of management practices on company performance – Operational management practices are well researched
– People management practices are often neglected
• Problem: – How can we model proactive customer service behaviour?
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Department Store Customer Service
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Department Store Customer Service
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Cargo Screening Processes at Calais Ferry Port
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Sustaining Urban Habitats
• For more information see: http://www.cs.nott.ac.uk/~pos/research.html
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Thanks to Anthony Beck (LUCAS) for the poster! 24
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Simulating Rail Passengers
• The rail network in the UK is fast approaching maximum capacity and passenger numbers are growing 6-7% per year
• One relatively simple (and therefore cheap) way to increase capacity of the rail network is to reduce loading/unloading times (dwell time)
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Simulating Rail Passengers
• The "social force model" (Helbing and Molnar 1995) assumes that the acceleration, deceleration and directional changes of pedestrians can be approximated by a sum of different forces, each capturing a different desire or interaction effect.
http://futurict.blogspot.it/2014/12/social-forces-revealing-causes-of.html
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Simulating Rail Passengers
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Modal Shift: From Road to Rail (with HF)
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SimPB: Simulating Peace Building
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SimPB: Simulating Peace Building
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Using a Hybrid Approach on Climate Assessment Modelling
• Global warming has been a profound indicator of human-induced climate change since the mid-20th century.
• At present, the integrated assessment models used by scientists and policy makers are mostly built using a SD approach, which views a system at an aggregate level.
• In our research we developed a Hybrid Climate Assessment Model (HCAM) , a fully integrated climate policy assessment tool which contains a System Dynamics climate-economy model and an agent-based population model.
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Using a Hybrid Approach on Climate Assessment Modelling
• Sector Boundary Map
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Using a Hybrid Approach on Climate Assessment Modelling
• Representation of the system
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Using a Hybrid Approach on Climate Assessment Modelling
• Representation of people
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Using a Hybrid Approach on Climate Assessment Modelling
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Using Simulation to Assist Recruitment in Seasonally Dependant Contact Centers
• The weather is unpredictable and can have a large impact on the profitability of seasonal businesses, particularly if staffing requirements are highly temperature-dependent
• An example for such a business is a company that provides boiler maintenance and repair services – In particular their Call Centre (CC) staffing level requirements depend
very much on the severity of the winter
– The likelihood of boilers breaking down during winter is correlated to the severity of the winter
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Using Simulation to Assist Recruitment in Seasonally Dependant Contact Centers
• Challenge – If recruitment starts too early then staff will have increased idle time
– If recruitment starts too late and the work increases faster than staff can cope, there will be lots of complaints and lost customers
• Aim – To develop a novel simulation tool that helps managers to make better
informed decisions about their CC recruitment needs (of permanent an temporary staff)
• Timing for hiring new staff
• Deciding about the optimal length of temporary contracts
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