Hybrid Metaheuristics

[EN]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 l...

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Authors: Blum, Christian, Raidl, Günther R.
Format: other
Publication Date:2016
Country:España
Institution:Consejo Superior de Investigaciones Científicas (CSIC)
Repository:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/243356
Online Access:http://hdl.handle.net/10261/243356
Access Level:Open access
Keyword:Heuristics
Metaheuristics
Hybrid metaheuristics
Dynamic programming
CPLEX
Constraint programming
Optimization
Cominatorial optimization
Neighborhood search
Integer linear programming
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spelling Hybrid MetaheuristicsPowerful Tools for OptimizationBlum, ChristianRaidl, Günther R.HeuristicsMetaheuristicsHybrid metaheuristicsDynamic programmingCPLEXConstraint programmingOptimizationCominatorial optimizationNeighborhood searchInteger linear programming[EN]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.Peer reviewedSpringer NatureBlum, Christian [0000-0002-1736-3559]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202120212016info:eu-repo/semantics/otherhttp://purl.org/coar/resource_type/c_2f33info:eu-repo/semantics/bookhttp://hdl.handle.net/10261/243356reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2433562026-05-22T06:33:51Z
dc.title.none.fl_str_mv Hybrid Metaheuristics
Powerful Tools for Optimization
title Hybrid Metaheuristics
spellingShingle Hybrid Metaheuristics
Blum, Christian
Heuristics
Metaheuristics
Hybrid metaheuristics
Dynamic programming
CPLEX
Constraint programming
Optimization
Cominatorial optimization
Neighborhood search
Integer linear programming
title_short Hybrid Metaheuristics
title_full Hybrid Metaheuristics
title_fullStr Hybrid Metaheuristics
title_full_unstemmed Hybrid Metaheuristics
title_sort Hybrid Metaheuristics
dc.creator.none.fl_str_mv Blum, Christian
Raidl, Günther R.
author Blum, Christian
author_facet Blum, Christian
Raidl, Günther R.
author_role author
author2 Raidl, Günther R.
author2_role author
dc.contributor.none.fl_str_mv Blum, Christian [0000-0002-1736-3559]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Heuristics
Metaheuristics
Hybrid metaheuristics
Dynamic programming
CPLEX
Constraint programming
Optimization
Cominatorial optimization
Neighborhood search
Integer linear programming
topic Heuristics
Metaheuristics
Hybrid metaheuristics
Dynamic programming
CPLEX
Constraint programming
Optimization
Cominatorial optimization
Neighborhood search
Integer linear programming
description [EN]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.
publishDate 2016
dc.date.none.fl_str_mv 2016
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/other
http://purl.org/coar/resource_type/c_2f33
dc.type.openaire.fl_str_mv info:eu-repo/semantics/book
format other
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/243356
url http://hdl.handle.net/10261/243356
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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