Multi-Level Lot Sizing and Scheduling - Kimms, Alf

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Résumé :
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Sommaire:
1 Introduction.- 1.1 Problem Context.- 1.2 Problem Outline and General Issues.- 1.3 Case Descriptions.- 1.4 Current Practice and Motivation.- 1.5 Chapter Synopsis.- 2 Literature Review.- 2.1 Scope of the Review.- 2.2 Contributions of General Interest.- 2.3 Dynamic Demand, Unlimited Capacity.- 2.4 Dynamic Demand, Scarce Capacity.- 2.5 Intermediate Results.- 3 Problem Specifications.- 3.1 Basic Assumptions.- 3.2 Multiple Machines.- 3.3 Problem Insights.- 3.4 Parallel Machines.- 3.5 Multiple Resources.- 3.6 Partially Renewable Resources.- 4 Instance Generation.- 4.1 Methods.- 4.2 Experimental Design for the PLSP-MM.- 4.3 A Comparison of Computing Machines.- 5 Lower Bounds.- 5.1 Network Representations.- 5.2 Capacity Relaxation.- 5.3 Lagrangean Relaxation.- 5.4 Summary of Evaluation.- 6 Multiple Machines.- 6.1 Unsuccessful Attempts.- 6.2 Common Construction Principles.- 6.3 Randomized Regret Based Sampling.- 6.4 Cellular Automata.- 6.5 Genetic Algorithms.- 6.6 Disjunctive Arc Based Tabu Search.- 6.7 Demand Shuffle.- 6.8 Summary of Evaluation.- 6.9 Some Tests with Large Instances.- 7 Parallel Machines.- 7.1 Related Topics: Job Scheduhng.- 7.2 A Demand Shuffle Adaption.- 7.3 Preliminary Experimental Evaluation.- 8 Multiple Resources.- 8.1 Related Topics: Project Scheduling.- 8.2 A Demand Shuffle Adaption.- 8.3 Preliminary Experimental Evaluation.- 9 Partially Renewable Resources.- 9.1 Related Topics: Course Scheduling.- 9.2 A Demand Shuffle Adaption.- 9.3 Preliminary Experimental Evaluation.- 10 Rolling Planning Horizon.- 10.1 Literature Review.- 10.2 Stability Measures.- 10.3 Pitfalls: Initial Inventory.- 11 Method Selection Guidelines.- 11.1 Basic Ideas.- 11.2 Instance Characterization.- 12 Research Opportunities.- 12.1 Extensions.- 12.2 Linkages to Other Areas.- 13 Conclusion.- A Lower Bounds for the PLSP-MM.- A.l LP-Relaxation: PLSP-Model.- A.2 LP-Relaxation: Plant Location Model.- A.3 Capacity Relaxation.- A. 4 Lagrangean Relaxation.- B Upper Bounds for the PLSP-MM.- B. l Randomized Regret Based Sampling.- B.2 Cellular Automaton.- B.3 Genetic Algorithm.- B.4 Disjunctive Arc Based Tabu Search.- B.5 Demand Shuffle.- C PLSP-PM: Demand Shuffle.- D PLSP-MR: Demand Shuffle.- E PLSP-PRR: Demand Shuffle.- List of Tables.- List of Figures.