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Hybrid Metaheuristics
ISBN-13:
9783319308838
Veröffentl:
2016
Seiten:
157
Autor:
Christian Blum
Serie:
Artificial Intelligence: Foundations, Theory, and Algorithms
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:
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.
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.
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