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Informationen zum Autor Pierre Lopez is a researcher within the Laboratory for Analysis and Architecture of Systems at the French National Center for Scientific Research (LAAS-CNRS). He is also head of the MOGISA group (Modeling, Optimization and Integrated Management of Systems of Activities). François Roubellat is also a researcher within LAAS-CNRS. His research is focused on Decision Support Systems for activity scheduling with resource constraints. Klappentext The performance of an company depends both on its technological expertise and its managerial and organizational effectiveness. Production management is an important part of the process for manufacturing firms. The organization of production relies in general on the implementation of a certain number of basic functions, among which the scheduling function plays an essential role. This title presents recently developed methods for resolving scheduling issues. The basic concepts and the methods of production scheduling are introduced and advanced techniques are discussed, providing readers with a comprehensive and accessible guide to employing this process. Zusammenfassung Scheduling is an important tool for manufacturing and engineering! where it can have a major impact on the productivity of a process. This title presents recently developed methods for resolving scheduling issues. Inhaltsverzeichnis Preface xiii Chapter 1. Statement of Production Scheduling 1 François ROUBELLAT and Pierre LOPEZ Chapter 2. Basic Concepts and Methods in Production Scheduling 5 Patrick ESQUIROL and Pierre LOPEZ 2.1. Introduction 5 2.2. Basic scheduling concepts 6 2.2.1. Tasks 6 2.2.2. Resources 7 2.2.3. Modeling 7 2.2.4. Resolution methods 12 2.2.5. Representation of solutions 15 2.3. Project scheduling 15 2.3.1. Modeling 16 2.3.2. Resolution 17 2.4. Shop scheduling 20 2.4.1. Introduction 20 2.4.2. Basic model 20 2.4.3. One-machine problem 21 2.4.4. Parallel machine problems 22 2.4.5. Flow shop 24 2.4.6. Job shop 26 2.5. Conclusion 29 2.6. Bibliography 29 Chapter 3. Metaheuristics and Scheduling 33 Marino WIDMER, Alain HERTZ and Daniel COSTA 3.1. Introduction 33 3.2. What is a combinatorial optimization problem? 34 3.3. Solution methods for combinatorial optimization problems 34 3.4. The different metaheuristic types 36 3.4.1. The constructive approach 36 3.4.2. Local search approach 37 3.4.3. The evolutionary approach 48 3.4.4. The hybrid approach 54 3.5. An application example: job shop scheduling with tooling constraints 55 3.5.1. Traditional job shop modeling 57 3.5.2. Comparing both types of problems 59 3.5.3. Tool switching 60 3.5.4. TOMATO algorithm 61 3.6. Conclusion 62 3.7. Bibliography 63 Chapter 4. Genetic Algorithms and Scheduling 69 Marie-Claude PORTMANN and Antony VIGNIER 4.1. Introduction 69 4.1.1. Origin of genetic algorithms 69 4.1.2. General principles of genetic algorithms 69 4.1.3. Schema theorem 72 4.1.4. Chapter presentation 73 4.2. One-machine problems 73 4.2.1. Example 1: total time and setup times 73 4.2.2. Example 2: sum of weighted tardiness 79 4.2.3. Example 3: sum of weighted tardiness and setup times 83 4.3. Job shop problems 85 4.4. Hybrid flow shop 89 4.4.1. Specific case: one-stage total duration problem 89 4.4.2. General case: k stages total duration problem 93 4.5. Hybrid genetic algorithms 99 4.5.1. Hybridization with other metaheuristics 99 4.5.2. Hybridization with combinatorial optimization methods 100 4.6. Conclus...
