Artificial Intelligence: Foundations, Theory, and Algorithms

Hybrid Metaheuristics

Powerful Tools for Optimization

Autoren: Blum, Christian, Raidl, Günther R.

  • Authors among the leading researchers in this domain    
  • Reflects the shift to problem-oriented rather than algorithm-oriented approaches
  • Valuable for researchers and graduate students in optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation 
Weitere Vorteile

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eBook 65,44 €
Preis für Deutschland (Brutto)
  • ISBN 978-3-319-30883-8
  • Versehen mit digitalem Wasserzeichen, DRM-frei
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  • eBooks sind auf allen Endgeräten nutzbar
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Hardcover 82,38 €
Preis für Deutschland (Brutto)
  • ISBN 978-3-319-30882-1
  • Kostenfreier Versand für Individualkunden weltweit
  • Gewöhnlich versandfertig in 3-5 Werktagen.
Über dieses Buch

This book explains the most prominent and some promising new, general techniques that combine metaheuristics with other optimization methods. A first introductory chapter reviews the basic principles of local search, prominent metaheuristics, and tree search, dynamic programming, mixed integer linear programming, and constraint programming for combinatorial optimization purposes. The chapters that follow present five generally applicable hybridization strategies, with exemplary case studies on selected problems: incomplete solution representations and decoders; problem instance reduction; large neighborhood search; parallel non-independent construction of solutions within metaheuristics; and hybridization based on complete solution archives.     

The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains.

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Inhaltsverzeichnis (7 Kapitel)

  • Introduction

    Blum, Christian (et al.)

    Seiten 1-26

  • Incomplete Solution Representations and Decoders

    Blum, Christian (et al.)

    Seiten 27-44

  • Hybridization Based on Problem Instance Reduction

    Blum, Christian (et al.)

    Seiten 45-62

  • Hybridization Based on Large Neighborhood Search

    Blum, Christian (et al.)

    Seiten 63-82

  • Making Use of a Parallel, Non-independent, Construction of SolutionsWithin Metaheuristics

    Blum, Christian (et al.)

    Seiten 83-99

Dieses Buch kaufen

eBook 65,44 €
Preis für Deutschland (Brutto)
  • ISBN 978-3-319-30883-8
  • Versehen mit digitalem Wasserzeichen, DRM-frei
  • Erhältliche Formate: PDF
  • eBooks sind auf allen Endgeräten nutzbar
  • Sofortiger eBook Download nach Kauf
Hardcover 82,38 €
Preis für Deutschland (Brutto)
  • ISBN 978-3-319-30882-1
  • Kostenfreier Versand für Individualkunden weltweit
  • Gewöhnlich versandfertig in 3-5 Werktagen.
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Bibliografische Information

Bibliographic Information
Buchtitel
Hybrid Metaheuristics
Buchuntertitel
Powerful Tools for Optimization
Autoren
Titel der Buchreihe
Artificial Intelligence: Foundations, Theory, and Algorithms
Copyright
2016
Verlag
Springer International Publishing
Copyright Inhaber
Springer International Publishing Switzerland
eBook ISBN
978-3-319-30883-8
DOI
10.1007/978-3-319-30883-8
Hardcover ISBN
978-3-319-30882-1
Buchreihen ISSN
2365-3051
Auflage
1
Seitenzahl
XVI, 157
Anzahl der Bilder und Tabellen
11 schwarz-weiß Abbildungen, 9 Abbildungen in Farbe
Themen