article

Variable Neighborhood Decomposition Search

Authors:

Nenad Mladenović,

Dionisio Perez-BritosAuthors Info & Claims

Journal of Heuristics, Volume 7, Issue 4

Pages 335 - 350

https://doi.org/10.1023/A:1011336210885

Published: 01 July 2001 Publication History

Abstract

The recent Variable Neighborhood Search (VNS) metaheuristic combines local search with systematic changes of neighborhood in the descent and escape from local optimum phases. When solving large instances of various problems, its efficiency may be enhanced through decomposition. The resulting two level VNS, called Variable Neighborhood Decomposition Search (VNDS), is presented and illustrated on the p-median problem. Results on 1400, 3038 and 5934 node instances from the TSP library show VNDS improves notably upon VNS in less computing time, and gives much better results than Fast Interchange (FI), in the same time that FI takes for a single descent. Moreover, Reduced VNS (RVNS), which does not use a descent phase, gives results similar to those of FI in much less computing time.

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Published In

cover image Journal of Heuristics

Journal of Heuristics Volume 7, Issue 4

July 2001

102 pages

ISSN:1381-1231

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Copyright © Copyright © 2001 Kluwer Academic Publishers.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 July 2001

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