Towards the reconfiguration of supply chains Thursday 28th November 2013 École nationale...

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Towards the reconfiguration of supply chains Thursday 28th November 2013 École nationale supérieure des mines de Saint-Étienne PhD Student : AKRAM CHIBANI Thesis advisors : M. Alexandre DOLGUI M. Henri PIERREVAL M. Xavier DELORME 1

Transcript of Towards the reconfiguration of supply chains Thursday 28th November 2013 École nationale...


Towards the reconfiguration of supply chains

Thursday 28th November 2013

École nationale supérieure des mines de Saint-Étienne

PhD Student : AKRAM CHIBANIThesis advisors : M. Alexandre DOLGUI


Dynamic Optimization

Introduction: The Supply chain

Agility, Flexibility, Adaptation, Reconfiguration

Suppliers Selection Problem

Conclusion & Research directions




• In order to survive in a changing environment, supply chains must be able to respond quickly to changes.

• Dynamic considerations have led researchers to find suitable models for the supply chain system. However, due to its complexity, reaction to changes is difficult to implement.

• Supply chains are complicated dynamical systems due to many factors, e.g. the competition between companies, the globalization, demand fluctuations, sales forecasting.


Evolution Context

Before 1975 1975-1990 1990-Now

Supply/Demand Demand > Supply Supply = Demand Demand < Supply

Demand Deterministic Prevision Uncertainties

Producer priority Quantity Quantity and flexibility fast response

Product life cycle Long - Short

Market National Continental Global

Customer/Supplier The producer is the king The customer is the king Cooperation

Goal Mass Production Supply chain optimization


US auto man.



Toyota“Toyota helped us dramatically improve our production system. We started by making one component, and as we improved, [Toyota] rewarded us with orders for more components. Toyota is our best customer.”

- Senior executive, supplier to Ford, GM, Chrysler, and Toyota, July 2001**

“The Big Three [US automakers] set annual cost-reduction targets [for the parts they purchase]. To realize those targets, they’ll do anything. [They’ve unleashed] a reign of terror, and it gets worse every year. You can’t trust anyone [in those companies]”

- Director, interior systems supplier to Ford, GM, and Chrysler, October 1999*

* And ** Source: Building Deep Supplier Relationships, HBR, December 2004

Arm’s Length




I'm glad that the hole is not on our side!

Losing Sight of the Common Objective


The definition of the supply chain has adapted to the evolution of the market and several definitions have been cited by researchers throughout years.

Supply chain is an integrated manufacturing process wherein raw materials are converted into final products, then delivered to customers.

[Beamon, 1998]

Supply chain is "a network of organizations, flow and process wherein a number of various enterprises (suppliers, manufacturers, distributors, and retailer) collaborate along the entire value chain to acquire raw materials, and to convert these raw materials into specified final products, and to deliver these final products to customers.“

[Ivanov, 2010]

Supply Chain: Definitions







The Supply Chain


Most of the works are related to the three main activities of the supply chain:• Production,• Storage,• Transport.

• Strategic level Design: determine the structure of the chain, in its topology and selection of stakeholders. Competitive advantages: analyze how the management of the supply chain can develop or improve business competitiveness. Historical perspectives: focuses on the development of business strategies for supply chain.

• Tactical Level Relationship development. Integrated operations. Transportation and distribution.

• Operational level Inventory Management and control Production ,planning and Scheduling Information sharing, coordination and monitoring

[Ganeshan, 1998] dressed and classified these issues based on the decision level.

Supply Chain issues


• Deterministic models in which the input data are supposed known and specified,

• Stochastic models where at least one of the input data are unknown and are assumed to follow a particular probability distribution,

• Economic models which are used generally to model the buyer-supplier relationship in the supply,

• Simulation models which are used to evaluate the effect of various supply chain strategies on demand amplification by integrating the flow of information throughout the chain, implementing a just in time inventory policy to reduce time delays, modifying the parameters of the existing order quantity procedures, etc.

[Beamon, 1998]• Hybrid models have allowed developing methods suited to respond to changes, essentially for issues dealing with all decisions level.

[Ding, 2003]

Supply Chain models


Structures and performances of supply chain are directly affected by changes.

Companies must adapt to:• changing economic conditions (e.g. changes in costs, increased prices of raw materials), • technical problems (e.g. limited capacity, transport delays) ,• the competitive constraints (e.g. report quality/ attractive price, technology watch, choice of suppliers).The vocabulary used by researches to define response to changes is not clear and many tools emerge from the increasing complexity of supply chain networks which is imputable to vagueness of information and the size of the problems.

Terms like flexibility, agility, adaptability and reconfigurability are highlighted in the literature to define these issues.

The response to changes


Introduction : The supply chain

Dynamic Optimization

Agility, Flexibility , Adaptation, Reconfiguration

Suppliers Selection Problem

Conclusion & Research directions




The flexibility is “ A property of a supply chain concerning its ability to change itself quickly structurally and functionally depending on the current execution state, reaching supply chain management goals by a change of supply chain structures and behavior.“

[Ivanov, 2010]


Agility is the ability of an organization to respond rapidly to changes in demand, both in terms of volume and variety.

[Christopher, 2000]

The ability to respond quickly and adequately to short-term changes in demand, supply or the environment. It is derived from the flexibility, responsiveness and effectiveness of the supply chain.

[Charles, 2010]

The agile supply chain must necessarily promote the various flows between suppliers and customers.

[lee, 2004]


Fig.1 Agility by A. Charles, 2010



The ability to adjust the supply chain's design to meet structural shifts in markets and modify the supply network to reflect changes in strategies, technologies and products.

[lee, 2004]


Reconfigurability (Reconfiguration)

A reconfigurable system is a system designed for rapid adjustment of production capacity and functionality, in response to new circumstances, by rearrangement or change of its components.

[Mehrabi et al, 2000]

Components may be all entities which form the logistic network e.g. supplier, manufactures, retailers, distributors and customers.

Circumstances may be the change of products, collaboration with new suppliers, localization of new sites, etc.

Supply chain context:


A Comparative study of adaptability and flexibility in distributed manufacturing supply chains.Agent-based simulation is employed in this study to model the operations of supply chains. Authors assume that flexibility and adaptability simultaneously can reduce the total system cost based on a stochastic model.

[Chan & Chan, 2010]

The reconfiguration of the supply network of an enterprise to cope with flexible strategies, to illustrate the influence in a dynamic global market environment on the structure of the supply chain.They treat in their paper two types of strategies, flexible procurement and flexible manufacturing in order to evaluate the supply network flexibility in terms of numerical comparison based on an indicator called "suitability of the reconfiguration of supply network".

[Oh et al., 2011]

An approach of a new model and tools for the planning and control of adaptive supply chain to take into account system elements activity.They proposed a multi-structural framework to have links to comprehensive uncertainty analysis, supply chain execution and the reconfiguration of supply chain.

[Ivanov et al., 2010]

The response to changes in the literature


The dynamism of supply chains

The influence of the volatile aspect of some factors shows the complexity of the distribution network to manage. It is obvious that one of the aspects of the supply chain is uncertainty.

The uncertainty "characterizes the incompleteness of knowledge about system's environment and conditions of its development."

[Ivanov, 2010]

Dynamism is "A system's change and evolution in the form of changes in object and process states in space and time as driven by perturbation influences and control influences of both planned control actions to transit a system from a current state to a desired one and adaptation control action to adapt a system to a change execution environment.“

[Ivanov, 2010]18

According to [Ivanov, 2010], the synergy between all these aspects allows a dynamic execution, and "it is unwound over different time horizons."

The author dresses a number of features to characterize a dynamic Supply chain system:

• The process of supply chain execution is non-stationary and non-linear.

• There are no strict criteria of decision-making for supply chain management and no a "priori" information about many supply chain parameters.

The dynamism of supply chains

Fig.2 The dynamism of the supply chain


Introduction : The supply chain

Dynamic Optimization

Agility, Flexibility, Adaptation, Reconfiguration

Suppliers Selection Problem

Conclusion & Research directions



Dynamic optimization

Dynamic optimization problem is a problem where the objective function or the restrictions change over time and where the changes are unknown.

[Cruz, 2010]

The goal of the issues dealing with dynamic optimization problems is no longer to locate a stationary optimal solution, but to track its movement through the solution and time space as closely as possible.

Generally there is not much time between two subsequent decisions time, restarting optimization at every changes is often undesirable.


Dynamic optimization

The lack of visibility known by the term of "myopia" does not predict the behavior of the models to the end of a given period. In other words, since the dynamic changes are unknown beforehand the problem has to be solved over time.

Optimum behavior in the search space over time.

Fig.3 Optimum behavior in time


Inventory management and dynamic vehicles routing problem represent the two most studied in industry.

The VRP (Vehicle routing problem) is to determine touring a fleet of vehicles to deliver a set of customers, while minimizing the cost of delivery of the goods. A dynamic variant of the problem is that the rides of different vehicles from a central repository are represented by cycles whose vertices correspond to customers. The dynamic nature of this problem is that customers can be added or removed unexpectedly .

[Li, 2006]The goal in Inventory management problems is to manage the inventory of an actor. He must ensure that the inventory is filled enough to meet customers demand without overstocking. Decision related to this case faces the problem of which quantity of products to command to maximize profit? And which suppliers select to ship this quantity?

[Bosman, 2007]

Supply Chain & Dynamic Optimization


Introduction : The supply chain

Dynamic Optimization

Agility, Flexibility , Adaptation, Reconfiguration

Suppliers Selection Problem

Conclusion & Research directions




Supplier selection problem is one of numerous problems dealing with the structure of the supply chain.

Supplier's capacity, lead time and various cost parameters are subject to change over time.

Suppliers selection problem

The optimal set of supplier can change from a period to another. In the literature this kind of problems is known as Dynamic Supplier Selection Problem.

Suppliers selection problem

[Ghodsypour, 1998] presents a decision support system using an integrated analytic hierarchy process (AHP) and linear programming.

[wu, 2009] used an integrated multi-objective decision-making process for supplier selection with bundling problem. Analytic network process (ANP) and mixed integer programming (MIP) are provided to optimize the selection of supplier.

[ding, 2005] used an optimization via simulation approach using genetic algorithm for supplier selection issue. Discrete-event simulation is used for performance evaluation of a supplier portfolio and the genetic algorithm is proposed for optimum portfolio identification based on performance index estimated by the simulation.


Decision time



Decision time



Period T

δ 0 δ 1 δ k δ n

Initial Configuration

:Initial set of




Purchase Cost

Assignment Cost

Problem formulation



The formulation involves minimizing the total cost which is raised due to unit cost of product and assignment cost at supplier s for entire sub-period δ

The satisfaction of the demand

The capacity restriction for each supplier s

Enforces the binary nature on Vs

Denotes the entire nature on Qs

Problem formulation


Dynamic approach

The literature review of [Nguyen, 2012] listed approaches dealing with changes in several issues :

• Detecting changes

• Introducing diversity when changes occur

• Maintaining diversity during the search

• Memory approaches

• Prediction approaches

• Self-adaptive methods

• Multi-population approaches

Algorithm. Using explicit memory

1. Initialize: (a)Initialize the population (b) Initialize the explicit memory

2. For each generation (a) Evaluate each member of the population (b) Update the memory(c) Reproduce a new population (d) Use information from the memory to update the new population(e) Return to step 2a


Dynamic approach

Fig.4 A Dynamic approach


Genetic Algorithm

“Genetic algorithms are search methods based on principles of natural selection and genetics". They encode the decision variables of a search problem into "finite-length strings of alphabets of certain cardinality". The strings which are candidate solutions to the search problem are chromosomes, the alphabets are genes and the values of genes are alleles.

[Goldberg, 1989]

Fig.5 Genetic Algorithm


Genetic Algorithm

The “ mutation  ”

The “ crossover  ”  

“Representation scheme”


10 20 10 10 5

15 25 0 5 5

-5 -5 0 5 0

5 20 10 20 5

10 20 1 5 5

0 0 9 5 0

5 20 10 20 5

10 20 10 5 5

0 0 0 5 0










Repair Algorithm

P = ∑ - Rj = 10

∑ Rj = -5


Introduction : The supply chain

Dynamic Optimization

Agility, Flexibility, Adaptation, Reconfiguration

Suppliers Selection Problem

Conclusion & Research directions




• Our aim is to find a response for two major questions: When and How should we reconfigure supply chain following time.

• Based on the optimum behavior after each change, we wish to be able to determine the time and the way in which we proceed to select supplier for each forecast period.

• The supply chain is considered as a theoretic system that does not reflect the reality of the changing environment.

• Supply chains must be able to change quickly and adapt their network to cope with changing market conditions.

• Supply chain problems, as a result of changing situation, need more efficient methods to respond effectively to perturbation.


Research directions

• We are planning to extend and implement the mathematical model to make in consideration more operations on supply chain.

• An algorithm-based memory that detects changes and keeps the best individuals over time can converge quickly to the best solution as it was demonstrated in many Benchmarks.

• Other approaches adapted for dynamic optimization problem, like anticipation, need to be developed if we want to take into account further operations in a global supply chain.

• Complexity can also be applied to the parameters of the problem. The variation of demand, for example, in each sub-period involves changes at the genetic algorithm as well as a possible reconfiguration costs.