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Hybrid Metaheuristics By Christian Blum

Hybrid Metaheuristics by Christian Blum

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Summary

Optimization problems are of great importance across a broad range of fields. This book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments.

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Hybrid Metaheuristics Summary

Hybrid Metaheuristics: An Emerging Approach to Optimization by Christian Blum

Optimization problems are of great importance across a broad range of fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. This book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments. The authors involved in this book are among the top researchers in their domain.

Table of Contents

Hybrid Metaheuristics: An Introduction.- Combining (Integer) Linear Programming Techniques and Metaheuristics for Combinatorial Optimization.- The Relation Between Complete and Incomplete Search.- Hybridizations of Metaheuristics With Branch & Bound Derivates.- Very Large-Scale Neighborhood Search: Overview and Case Studies on Coloring Problems.- Hybrids of Constructive Metaheuristics and Constraint Programming: A Case Study with ACO.- Hybrid Metaheuristics for Packing Problems.- Hybrid Metaheuristics for Multi-objective Combinatorial Optimization.- Multilevel Refinement for Combinatorial Optimisation: Boosting Metaheuristic Performance.

Additional information

NLS9783642096976
9783642096976
3642096972
Hybrid Metaheuristics: An Emerging Approach to Optimization by Christian Blum
New
Paperback
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
2010-11-24
290
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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