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Variable Neighborhood Search

Pierre Hansen () and Nenad Mladenović
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Pierre Hansen: GERAD and HEC Montreal
Nenad Mladenović: School of Mathematics, Brunel University

Chapter Chapter 12 in Search Methodologies, 2014, pp 313-337 from Springer

Abstract: Abstract Variable neighborhood search (VNS) is a metaheuristic, or framework for building heuristics, which exploits systematically the idea of neighborhood change, both in the descent to local minima and in the escape from the valleys which contain them. In this tutorial we first present the ingredients of VNS, i.e. variable neighborhood descent (VND) and Reduced VNS (RVNS) followed by the basic and then the general scheme of VNS itself which contain both of them. Extensions are presented, in particular Skewed VNS which enhances exploration of far away valleys andvariable neighborhood decomposition search (VNDS), a two-level scheme for solution of large instances of various problems. In each case, we present the scheme, some illustrative examples and questions to be addressed in order to obtain an efficient implementation.

Keywords: Local Search; Local Optimum; Travel Salesman Problem; Constructive Heuristic; Variable Neighborhood Descent (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-6940-7_12

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DOI: 10.1007/978-1-4614-6940-7_12

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