Description
Springer Hybrid Metaheuristics An Emerging Approach To Optimization 2008 Edition by Christian Blum Andrea Roli Michael Sampels
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.