Evolutionary scheduling

Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are ofte...

Ausführliche Beschreibung

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Bibliographische Detailangaben
1. Verfasser: Dahal, Keshav (Verlagsleitung)
Weitere Verfasser: Tan, Kay Chen (HerausgeberIn, Verlagsleitung), Cowling, Peter I. (HerausgeberIn), Cowling, Peter Ivan, 19..- (Verlagsleitung)
Format: Livre numérique
Sprache:Anglais
Veröffentlicht: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Ausgabe:1st ed. 2007.
Schriftenreihe:Studies in Computational Intelligence 49
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Edition sous un autre format:• Evolutionary scheduling, edited by Keshav Dahal, Kay Chen Tan and Peter I. Cowling, Berlin, Springer, 2007, xi, 628 p., Studies in computational intelligence, 978-3-540-48582-7
• Evolutionary Scheduling, Texte imprimé, 9783540832461
• Evolutionary Scheduling, Texte imprimé, 9783642080173
• Evolutionary scheduling, edited by Keshav Dahal, Kay Chen Tan and Peter I. Cowling, Berlin, Springer, 2007, xi, 628 p., Studies in computational intelligence, 978-3-540-48582-7
Beschreibung
Zusammenfassung:Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are often inadequate at solving them effectively. With the advent of computation intelligence, there is renewed interest in solving scheduling problems using evolutionary computational techniques. These techniques, which include genetic algorithms, genetic programming, evolutionary strategies, memetic algorithms, particle swarm optimization, ant colony systems, etc, are derived from biologically inspired concepts and are well-suited to solve scheduling problems since they are highly scalable and flexible in terms of handling constraints and multiple objectives. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling, and demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems. The intended readers of this book are engineers, researchers, practitioners, senior undergraduates, and graduate students who are interested in the field of evolutionary scheduling
Beschreibung:Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
ISBN:9783540485841
ISSN:1860-9503
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