Variable neighborhood search: basics and variants

Variable neighborhood search: basics and variants Variable neighborhood search (VNS) is a framework for building heuristics, based upon systematic changes of neighborhoods both in a descent phase, to find a local minimum, and in a perturbation phase to escape from the corresponding valley. In this paper, we present some of VNS basic schemes as well as several VNS variants deduced from these basic schemes. In addition, the paper includes parallel implementations and hybrids with other metaheuristics. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png EURO Journal on Computational Optimization Springer Journals

Variable neighborhood search: basics and variants

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2016 by EURO - The Association of European Operational Research Societies
Subject
Business and Management; Operations Research/Decision Theory; Operations Management; Operations Research, Management Science; Optimization
ISSN
2192-4406
eISSN
2192-4414
D.O.I.
10.1007/s13675-016-0075-x
Publisher site
See Article on Publisher Site

Abstract

Variable neighborhood search (VNS) is a framework for building heuristics, based upon systematic changes of neighborhoods both in a descent phase, to find a local minimum, and in a perturbation phase to escape from the corresponding valley. In this paper, we present some of VNS basic schemes as well as several VNS variants deduced from these basic schemes. In addition, the paper includes parallel implementations and hybrids with other metaheuristics.

Journal

EURO Journal on Computational OptimizationSpringer Journals

Published: Aug 12, 2016

References

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