Authors: Hansen, Pierre
Mladenović, Nenad 
Affiliations: Mathematical Institute of the Serbian Academy of Sciences and Arts 
Title: Variable neighborhood search
Journal: Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques
First page: 211
Last page: 238
Issue Date: 1-Dec-2005
ISBN: 978-0-387-23460-8
DOI: 10.1007/0-387-28356-0_8
Variable Neighborhood Search (VNS) is a recent 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 (SVNS) which enhances exploration of far-away valleys and Variable 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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