Hybrid Metaheuristics : Powerful Tools for Optimization

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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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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

006.3 BLU h

Penerbit

Switzerland : Springer., 2016

Deskripsi Fisik

xvi, 157 hlm. : ilus. ; 25 cm

Bahasa

English

ISBN/ISSN

978-3-319-30882-1

Klasifikasi

006.3

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

Operations Research
Artificial Intelligence
Computational Intelligence
Mathematical optimization
Heuristic programming

Info Detail Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

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