Variable Neighborhood Search

Pierre Hansen (), Nenad Mladenović (), Jack Brimberg () and José A. Moreno Pérez ()
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Pierre Hansen: GERAD and Ecole des Hautes Etudes Commerciales
Nenad Mladenović: Brunel University-West London
Jack Brimberg: Royal Military College of Canada
José A. Moreno Pérez: IUDR and DEIOC, Universidad de La Laguna

Chapter Chapter 3 in Handbook of Metaheuristics, 2010, pp 61-86 from Springer

Abstract: Abstract Variable neighborhood search (VNS) is a metaheuristic for solving combinatorial and global optimization problems whose basic idea is a systematic change of neighborhood both within a descent phase to find a local optimum and in a perturbation phase to get out of the corresponding valley. In this chapter we present the basic schemes of VNS and some of its extensions. We then describe a recent development, i.e., formulation space search. We then present five families of applications in which VNS has proven to be very successful: (i) exact solution of large-scale location problems by primal–dual VNS; (ii) generation of feasible solutions to large mixed integer linear programs by hybridization of VNS and local branching; (iii) generation of good feasible solutions to continuous nonlinear programs; (iv) generation of feasible solutions and/or improved local optima for mixed integer nonlinear programs by hybridization of sequential quadratic programming and branch and bound within a VNS framework, and (v) exploration of graph theory to find conjectures, refutations, and proofs or ideas of proofs.

Keywords: Local Search; Mixed Integer Linear Programming; Variable Neighborhood Search; Global Optimization Problem; Extremal Graph (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1007/978-1-4419-1665-5_3

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