Supply chain management is a key topic for a large variety of strategic decision problems. It is essential in making efficient decisions related to the management of inventory and the delivery of final products to customers.
The focus of this book is the understanding of the supply chain taxonomy, the different levels of decision and the impact of one level on another depending on the modeling of the addressed objectives.
The authors explore the potential problems that can be addressed within the supply chain, such as the inventory, the transportation and issues of holding, and find applications in numerous fields of study, from cloud computing and networking through to industrial sciences.
The reader can find 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.
Table of Contents:
List of Figures ix
List of Tables xi
Glossary xiii
Introduction xv
Chapter 1. Preliminaries in Decision-Making 1
1.1. Introduction 1
1.2. Decision-making problems 2
1.3. Optimization modeling of a decision problem 3
1.3.1. Notation 4
1.3.2. Features of an optimization problem 5
1.3.3. A didactic example 6
1.4. Game theory modeling of a decision problem 7
1.4.1. Notation 7
1.4.2. The coalition formation problem 8
1.4.3. The stability concepts 10
1.5. Allocation methods 11
1.5.1. Shapley value allocation 11
1.6. Conclusion 12
Chapter 2. Introduction to Supply Chain Management 13
2.1. Introduction 13
2.2. Main elements of the supply chain 13
2.3. Main activities in the supply chain 18
2.3.1. The ordering problem 18
2.3.2. The warehousing problem 19
2.3.3. The transportation problem 19
2.3.4. The inventory problem 20
2.3.5. Computer science applications in supply chain management 21
2.4. Decision levels in the supply chain 22
2.4.1. Strategic level 23
2.4.2. Tactical level 23
2.4.3. Operational level 23
2.5. Conclusion 23
Chapter 3. The Ordering Problem 25
3.1. Introduction 25
3.2. Terminology 26
3.3. The one supplier–one retailer ordering problem 26
3.3.1. An example of the one–one ordering problem 28
3.3.2. Summary 28
3.4. The one supplier–multiple retailers ordering problem 29
3.4.1. Fixed purchasing price 30
3.4.2. An example of the 1 − n ordering problem 30
3.4.3. Quantity-dependent purchasing price 30
3.5. The multiple suppliers–one retailer ordering problem 31
3.6. The multiple suppliers–multiple retailers ordering problem 32
3.7. Conclusion 36
Chapter 4. The Warehousing Problem 37
4.1. Introduction 37
4.2. Problem description 38
4.2.1. Terminology 39
4.2.2. Inputs/outputs of the WP 40
4.2.3. WP variants 40
4.3. WP with variable cost/without conflicts 42
4.3.1. Mathematical formulation 42
4.3.2. An example 42
4.4. WP with fixed cost/without conflicts 44
4.4.1. Mathematical formulation 44
4.4.2. An example 44
4.5. WP with variable cost/with conflicts 46
4.5.1. Mathematical formulation 47
4.5.2. An example 47
4.6. WP with fixed cost/with conflicts 50
4.6.1. Mathematical formulation 50
4.6.2. An example 50
4.7. A DSS design for the warehousing problem 53
4.8. Example 54
4.9. Answer 55
4.10. Conclusion 56
Chapter 5. Inventory Management 57
5.1. Introduction 57
5.2. Definition of inventory management 58
5.3. Purposes of inventory 59
5.4. Inventory modeling 59
5.4.1. Terminology 60
5.4.2. Economic order quantity model 60
5.4.3. Examples 61
5.5. Conclusion 63
Chapter 6. The Delivery in the Supply Chain 65
6.1. Introduction 65
6.2. The delivery process in the SC 67
6.3. Problem description 68
6.3.1. Terminology 70
6.3.2. Inputs/outputs of the delivery 70
6.3.3. Delivery variants 70
6.4. First Variant: delivery with capacitated trucks 70
6.4.1. CVRP specification 71
6.4.2. Mathematical formulation of the CVRP 71
6.5. Second Variant: delivery with time windows 72
6.5.1. VRPTW specification 72
6.5.2. Mathematical formulation of the VRPTW 73
6.6. A real case study: the case of Tunisia 74
6.7. Alternative resolution approaches for the delivery problem 75
6.7.1. A tabu search approach for solving the delivery problem 75
6.7.2. A genetic algorithm for solving the delivery problem 76
6.8. A DSS design for the delivery problem 78
6.9. Conclusion 79
Bibliography 81
Index 85
About the Author :
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.
Review :
"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)
