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Variable Neighborhood Search

In: Search Methodologies

Author

Listed:
  • Pierre Hansen

    (GERAD and HEC Montreal)

  • Nenad Mladenović

    (SANU, GERAD and Mathematical Institute)

Abstract

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.

Suggested Citation

  • Pierre Hansen & Nenad Mladenović, 2005. "Variable Neighborhood Search," Springer Books, in: Edmund K. Burke & Graham Kendall (ed.), Search Methodologies, chapter 0, pages 211-238, Springer.
    • Handle: RePEc:spr:sprchp:978-0-387-28356-2_8
    DOI: 10.1007/0-387-28356-0_8
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