Evolutionary Search and the Job Shop Investigations on Genetic Algor
Production scheduling dictates highly constrained mathematical models with complex and often contradicting objectives. Evolutionary algorithms can be formulated almost independently of the detailed shaping of the problems under consideration. As one would
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Editors Wolfgang Domschke, Technical University of Darmstadt, Gemlany Andreas Drexl, University ofKiel, Germany Bernhard Fleischmann, University of Augsburg, Germany Hans-Otto Giinther, Technical University of Berlin, Germany Hartmut Stadtler, Technical University of Darmstadt, Germany
Titles in this Series
Erwin Pesch Learning in Automated Manufacturing 1994. XIV, 258 pages. ISBN 3-7908-0792-3 Rainer Kalisch Project Scheduling under Resource Constraints 1995. X, 212 pages. ISBN 3-7908-0829-6 Armin Scholl Balancing and Sequencing of Assembly Lines 1995. XVI, 306 pages. ISBN 3-7908-0881-4
Dirk C. Mattfeld
Evolutionary Search and the Job Shop Investigations on Genetic Algorithms for Production Scheduling With 62 Figures and 30 Tables
Springer-Verlag Berlin Heidelberg GmbH
Dr. Dirk C. Mattfeld University of Bremen Department of Economics 0-28334 Bremen, Germany
Die Deutsche Bibliothek - CIP-Einheitsaufnahme Mattfeld, Dirk C.: Evolutionary search and the job shop: investigations on genetic algorithms for production scheduling; with 30 tables / Dirk C. Mattfeld. - Heidelberg: Physica-VerI., 1996 (Production and logistics)
ISBN 978-3-7908-0917-6 ISBN 978-3-662-11712-5 (eBook) DOI 10.1007/978-3-662-11712-5 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in other ways, and storage in data banks. Duplication of this publication or parts thereofis only permitted under the provisions ofthe German Copyright Law of September9, 1965, in its version ofJune24, 1985, and a copyright fee must always be paid. Violations fall under the prosecution act of the German Copyright Law. © Springer-Verlag Berlin Heidelberg 1996 Originally published by Physica-Verlag Heidelberg in 1996.
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Preface
Production planning and control systems suffer from insufficient computational support in the field of production scheduling. Practical requirements dictate highly constrained mathematical models with complex and often contradicting objectives. Therefore scheduling even in computerized manufacturing systems still relies on simple priority rule based heuristics. Thus, we can expect a great so far unexploited optimization potential in manufacturing environments. Within the last decade academic research in scheduling has gained a significant progress due to modern Local Search based heuristics. Much effort has been put into suitable neighborhood definitions which go for the key feature of Local Search. However, it remains questionable whether this work can be transferred in order to fit the flexible requirements of production scheduling. Evolutionary Algorithms can b
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