Buch, Englisch, Band 57, 570 Seiten, Gewicht: 2160 g
Reihe: International Series in Operations Research & Management Science
Buch, Englisch, Band 57, 570 Seiten, Gewicht: 2160 g
Reihe: International Series in Operations Research & Management Science
ISBN: 978-1-4020-7263-5
Verlag: Springer Netherlands
The Handbook of Metaheuristics provides both the research and practitioner communities with a comprehensive coverage of the metaheuristic methodologies that have proven to be successful in a wide variety of real-world problem settings. Moreover, it is these metaheuristic strategies that hold particular promise for success in the future. The various chapters serve as stand alone presentations giving both the necessary background underpinnings as well as practical guides for implementation. In most settings a problem solver has an option as to which metaheuristic approach should be adopted for the problem at hand. Alternative methodologies typically exist that could be employed to produce high quality solutions. Often it becomes a matter of choosing one of several approaches that could be adopted. The very nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences. The chapters in this handbook are designed to facilitate this as well.
Table of contents:
List of Contributing Authors.- Preface.- 1. Scatter Search and Path Relinking: Advances and Applications.- 2. An Introduction to Tabu Search.- 3. Genetic Algorithms.- 4. Genetic Programming; 5. A Gentle Introduction to Memetic Algorithms.- 6. Variable Neighborhood Search.- 7. Guided Local Search.- 8. Greedy Randomized Adaptive Search Procedures.- 9. The Ant Colony Optimization Metaheuristic: Algorithms, Applications, and Advances.- 10. The Theory and Practice of Simulated Annealing.- 11. Iterated Local Search.- 12. Multi-Start Methods.- 13. Local Search and Constraint Programming.- 14. Constraint Satisfaction.- 15. Artificial Neural Networks for Combinatorial Optimization.- 16. Hyper-Heuristics: An Emerging Direction in Modern Search Technology.- 17. Parallel Strategies for Meta-Heuristics.- 18. Metaheuristic Class Libraries.- 19. Asynchronous Teams.- Index.
Zielgruppe
Research
