Authors: Hansen, Pierre
Mladenović, Nenad 
Title: Variable neighborhood search
Journal: Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques, Second Edition
First page: 313
Last page: 338
Issue Date: 1-Jan-2014
ISBN: 978-1-461-46940-7
DOI: 10.1007/978-1-4614-6940-7_12
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.
Publisher: Springer Link

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