Topic
Variable neighborhood search
About: Variable neighborhood search is a research topic. Over the lifetime, 2279 publications have been published within this topic receiving 55941 citations.
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TL;DR: This chapter presents the basic schemes of VNS and some of its extensions, and presents five families of applications in which VNS has proven to be very successful.
3,572 citations
Book•
01 Jan 2003
TL;DR: This book discusses Metaheuristic Class Libraries, Hyper-Heuristics, and Artificial Neural Networks for Combinatorial Optimization, which are concerned withMetaheuristic Algorithms and their applications in Search Technology.
Abstract: List of Contributing Authors. Preface. 1. Scatter Search and Path Relinking: Advances and Applications F. Glover, et al. 2. An Introduction to Tabu Search M. Grenreau. 3. Genetic Algorithms C. Reeves. 4. Genetic Programming 5. A Gentle Introduction to Memetic Algorithms P. Moscato, C. Cotta. 6. Variable Neighborhood Search P. Hansen, N. Mladenovic. 7. Guided Local Search C. Voudouris, E. Tsang. 8. Greedy Randomized Adaptive Search Procedures M. Resende, C. Ribeiro. 9. The Ant Colony Optimization Metaheuristic: Algorithms, Applications, and Advances M. Doringo, T. Stutzle. 10. The Theory and Practice of Simulated Annealing D. Henderson, et al. 11. Iterated Local Search H. Lourenco, et al. 12. Multi-Start Methods R. Marti 13. Local Search and Constraint Programming F. Focacci, et al. 14. Constraint Satisfaction E. Freuder, M. Wallace. 15. Artificial Neural Networks for Combinatorial Optimization J.-Y. Potvin, K. Smith. 16. Hyper-Heuristics: An Emerging Direction in Modern Search Technology E. Burke, et al. 17. Parallel Strategies for Meta-Heuristics T.G. Crainic, M. Toulouse. 18. Metaheuristic Class Libraries A. Fink, et al. 19. Asynchronous Teams S. Talukdar, et al. Index.
2,284 citations
TL;DR: In this article, a simple and effective metaheuristic for combinatorial and global optimization, called variable neighborhood search (VNS), is presented, which can easily be implemented using any local search algorithm as a subroutine.
1,824 citations
TL;DR: The Handbook now includes updated chapters on the best known metaheuristics, including simulated annealing, tabu search, variable neighborhood search, scatter search and path relinking, genetic algorithms, memetic algorithms, genetic programming, ant colony optimization, and multi-start methods.
Abstract: The first edition of the Handbook of Metaheuristics was published in 2003 under the editorship of Fred Glover and Gary A. Kochenberger. Given the numerous developments observed in the field of metaheuristics in recent years, it appeared that the time was ripe for a second edition of the Handbook. When Glover and Kochenberger were unable to prepare this second edition, they suggested that Michel Gendreau and Jean-Yves Potvin should take over the editorship, and so this important new edition is now available. Through its 21 chapters, this second edition is designed to provide a broad coverage of the concepts, implementations and applications in this important field of optimization. Original contributors either revised or updated their work, or provided entirely new chapters. The Handbook now includes updated chapters on the best known metaheuristics, including simulated annealing, tabu search, variable neighborhood search, scatter search and path relinking, genetic algorithms, memetic algorithms, genetic programming, ant colony optimization, multi-start methods, greedy randomized adaptive search procedure, guided local search, hyper-heuristics and parallel metaheuristics. It also contains three new chapters on large neighborhood search, artificial immune systems and hybrid metaheuristics. The last four chapters are devoted to more general issues related to the field of metaheuristics, namely reactive search, stochastic search, fitness landscape analysis and performance comparison.
1,208 citations