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Informationen zum Autor Jean-Charles Billaut is Professor in Computer Science in the Polytechnic School of the University of Tours, France. he teaches assembly language and operations research (graph theory and dynamic programming). He is also member of the board of the French OR Society (President in 2006 and 2007). Aziz Moukrim is Professor in Computer Science at the the University of Technology of Compiegne, France, and is a member of the UTC-CNFRS research laboratory (Heudiasyc). He teaches algorithmic and operations research (Scheduling, logistics and transportation systems). He is also co-leader of the CNRS Group (Scheduling and Transportation Networks). Eric Sanlaville is Associate Professor In Computer Science at the University of Clermont-Ferrand, France. He teaches algorithmics and operations research (both in deterministic and stochastic settings). He has been a member of het board of the French OR Society since 004. Klappentext Scheduling is a diverse research area, and scheduling problems arise from many application domains, such as production systems, logistics and computer science. Solving scheduling problems requires the use and knowledge of tools such as combinatorial optimization and exact or approximated algorithms. Flexibility is at the interface between predictive deterministic approaches and reactive or 'on-line' approaches. It exists when some information (which may not be complete or perfect) about the problem is known, which is fairly reliable and where it is likely that there will be a difference between the forecast plan and its execution. the purpose of flexibility is to provide on or more solutions tailored to the nature of the application in order to provide the ideal solution. Robustness, which characterizes the performance of an algorithm when data are subject to uncertainty, is defined as being able to be resistant to approximations and ignorance. This book focuses on the integration of flexibility and robustness considerations in the study of scheduling problems. After considering both flexibility and robustness, it then covers various scheduling problems, treating them with an emphasis on either flexibility o robustness, or both. Zusammenfassung Scheduling is a broad research area and scheduling problems arise from several application domains (production systems! logistic! computer science! etc.). Solving scheduling problems requires tools of combinatorial optimization! exact or approximated algorithms. Inhaltsverzeichnis Preface 13 Chapter 1. Introduction to Flexibility and Robustness in Scheduling 15 Jean-Charles BILLAUT, AzizMOUKRIM and Eric SANLAVILLE 1.1. Scheduling problems 15 1.1.1. Machine environments 16 1.1.2.Characteristics of tasks 17 1.1.3. Optimality criteria 18 1.2. Background to the study 19 1.3. Uncertainty management 20 1.3.1. Sources of uncertainty 21 1.3.2. Uncertainty of models 22 1.3.3. Possible methods for problem solving 23 1.3.3.1. Full solution process of a scheduling problem with uncertainties 23 1.3.3.2. Proactive approach 24 1.3.3.3. Proactive/reactive approach 24 1.3.3.4. Reactive approach 25 1.4. Flexibility 25 1.5. Robustness 26 1.5.1. Flexibility as a robustness indicator 27 1.5.2. Schedule stability (solution robustness) 28 1.5.3. Stability relatively to a performance criterion (quality robustness) 29 1.5.4. Respect of a fixed performance threshold 30 1.5.5. Deviation measures with respect to the optimum 30 1.5.6. Sensitivity and robustness 31 1.6. Bibliography 31 Chapter 2. Robustness in Operations Research and Decision Aiding 35 Bernard ROY 2.1. Overview 35 2.1.1. Robust in OR-DA with meaning? 36 2.1.2. Why the concern for robust...
