Supply Chain Management and its Applications in Computer Science

Saoussen Krichen is Associate Professor in Quantitative Methods at the University of Tunis in Tunisia. Her research interests include supply chains, optimization, game theory, decision support systems, and metaheuristics.Sihem Ben Jouida is a researcher at LARODEC laboratory at the University of Tunis in Tunisia. Her research interests include supply chains, optimization, game theory, decision support systems, and metaheuristics.

"The reader can fi nd each issue described and its positioning in the supply chain determined. A computer science framework is also developed to show how the use of electronic platforms can aid in the handling of these potential problems." (Zentralblatt MATH 2016)

• List of Figures ixList of Tables xiGlossary xiiiIntroduction xvChapter 1. Preliminaries in Decision-Making 11.1. Introduction 11.2. Decision-making problems 21.3. Optimization modeling of a decision problem 31.3.1. Notation 41.3.2. Features of an optimization problem 51.3.3. A didactic example 61.4. Game theory modeling of a decision problem 71.4.1. Notation 71.4.2. The coalition formation problem 81.4.3. The stability concepts 101.5. Allocation methods 111.5.1. Shapley value allocation 111.6. Conclusion 12Chapter 2. Introduction to Supply Chain Management 132.1. Introduction 132.2. Main elements of the supply chain 132.3. Main activities in the supply chain 182.3.1. The ordering problem 182.3.2. The warehousing problem 192.3.3. The transportation problem 192.3.4. The inventory problem 202.3.5. Computer science applications in supply chain management 212.4. Decision levels in the supply chain 222.4.1. Strategic level 232.4.2. Tactical level 232.4.3. Operational level 232.5. Conclusion 23Chapter 3. The Ordering Problem 253.1. Introduction 253.2. Terminology 263.3. The one supplier–one retailer ordering problem 263.3.1. An example of the one–one ordering problem 283.3.2. Summary 283.4. The one supplier–multiple retailers ordering problem 293.4.1. Fixed purchasing price 303.4.2. An example of the 1 − n ordering problem 303.4.3. Quantity-dependent purchasing price 303.5. The multiple suppliers–one retailer ordering problem 313.6. The multiple suppliers–multiple retailers ordering problem 323.7. Conclusion 36Chapter 4. The Warehousing Problem 374.1. Introduction 374.2. Problem description 384.2.1. Terminology 394.2.2. Inputs/outputs of the WP 404.2.3. WP variants 404.3. WP with variable cost/without conflicts 424.3.1. Mathematical formulation 424.3.2. An example 424.4. WP with fixed cost/without conflicts 444.4.1. Mathematical formulation 444.4.2. An example 444.5. WP with variable cost/with conflicts 464.5.1. Mathematical formulation 474.5.2. An example 474.6. WP with fixed cost/with conflicts 504.6.1. Mathematical formulation 504.6.2. An example 504.7. A DSS design for the warehousing problem 534.8. Example 544.9. Answer 554.10. Conclusion 56Chapter 5. Inventory Management 575.1. Introduction 575.2. Definition of inventory management 585.3. Purposes of inventory 595.4. Inventory modeling 595.4.1. Terminology 605.4.2. Economic order quantity model 605.4.3. Examples 615.5. Conclusion 63Chapter 6. The Delivery in the Supply Chain 656.1. Introduction 656.2. The delivery process in the SC 676.3. Problem description 686.3.1. Terminology 706.3.2. Inputs/outputs of the delivery 706.3.3. Delivery variants 706.4. First Variant: delivery with capacitated trucks 706.4.1. CVRP specification 716.4.2. Mathematical formulation of the CVRP 716.5. Second Variant: delivery with time windows 726.5.1. VRPTW specification 726.5.2. Mathematical formulation of the VRPTW 736.6. A real case study: the case of Tunisia 746.7. Alternative resolution approaches for the delivery problem 756.7.1. A tabu search approach for solving the delivery problem 756.7.2. A genetic algorithm for solving the delivery problem 766.8. A DSS design for the delivery problem 786.9. Conclusion 79Bibliography 81Index 85