Hybrid Metaheuristics

An Emerging Approach to Optimization
2008
ISBN: 978-3-540-78294-0
Verlag: Springer Berlin Heidelberg

Buch, Englisch, Band 114, 290 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 1320 g

Reihe: Studies in Computational Intelligence

Optimization problems are of great importance in many fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. Examples of metaheuristics are simulated annealing, tabu search, evolutionary computation, iterated local search, variable neighborhood search, and ant colony optimization. In recent years it has become evident that a skilled combination of a metaheuristic with other optimization techniques, a so called hybrid metaheuristic, can provide a more efficient behavior and a higher flexibility. This is because hybrid metaheuristics combine their advantages with the complementary strengths of, for example, more classical optimization techniques such as branch and bound or dynamic programming.

The authors involved in this book are among the top researchers in their domain. The 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.

Zielgruppe

Research

Autoren/Hrsg.

Blum, Christian

Sampels, Michael

Roli, Andrea

Fachgebiete

• Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
• Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computer-Aided Design (CAD)
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik Mathematik Operations Research
• Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure

Inhaltsverzeichnis

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.