Wir verwenden Cookies und Analyse-Tools, um die Nutzerfreundlichkeit der Internet-Seite zu verbessern und für Marketingzwecke. Wenn Sie fortfahren, diese Seite zu verwenden, nehmen wir an, dass Sie damit einverstanden sind. Zur Datenschutzerklärung.
Hybrid Metaheuristics
Details
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.
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
Autorentext
Inhalt
Introduction.- Incomplete Solution Representations and Decoders.- Hybridization Based on Problem Instance Reduction.- Hybridization Based on Large Neighborhood Search.- Making Use of a Parallel, Non-independent, Construction of Solutions Within Metaheuristics.- Hybridization Based on Complete Solution Archives.- Further Hybrids and Conclusions.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783319809076
- Sprache Englisch
- Auflage Softcover reprint of the original 1st edition 2016
- Größe H235mm x B155mm x T10mm
- Jahr 2018
- EAN 9783319809076
- Format Kartonierter Einband
- ISBN 3319809075
- Veröffentlichung 30.05.2018
- Titel Hybrid Metaheuristics
- Autor Günther R. Raidl , Christian Blum
- Untertitel Powerful Tools for Optimization
- Gewicht 277g
- Herausgeber Springer International Publishing
- Anzahl Seiten 176
- Lesemotiv Verstehen
- Genre Informatik