Open Access
EURO Journal on Computational Optimization, volume 5, issue 3, pages 423-454
Variable neighborhood search: basics and variants
PIERRE HANSEN
1
,
N. Mladenovic
2
,
Raca Todosijevic
2
,
Saïd Hanafi
2
1
GERAD and HEC Montréal, Montreal, Canada
|
2
LAMIH-UVHC, CNRS UMR 8201, Valenciennes Cedex 9, France
|
Publication type: Journal Article
Publication date: 2017-09-01
scimago Q1
SJR: 0.983
CiteScore: 3.5
Impact factor: 2.6
ISSN: 21924406, 21924414
Computational Mathematics
Control and Optimization
Modeling and Simulation
Management Science and Operations Research
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.
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