Authors: Urošević, Dragan 
Todosijević, Raca 
Mladenović, Nenad 
Brimberg, Jack
Affiliations: Computer Science 
Mathematical Institute of the Serbian Academy of Sciences and Arts 
Title: Variable Neighborhood Search
Series/Report no.: Springer Optimization and Its Applications
First page: 151
Last page: 189
Related Publication(s): Discrete Diversity and Dispersion Maximization
Issue Date: 1-Jan-2023
ISBN: 978-3-031-38309-0
ISSN: 1931-6828
DOI: 10.1007/978-3-031-38310-6_8
Variable neighborhood search (VNS) is a framework for building heuristics based upon systematic changes of neighborhoods both in a descent phase, to find a local minimum, and in a perturbation phase to emerge from the corresponding valley. In this chapter, we provide an overview of different VNS variants and describe how they can be used to solve diversity (dispersion) problems. More precisely, we present different neighborhood structures that may be exploited and show how they can be organized within variable neighborhood descent and variable neighborhood search heuristics. Finally, we provide insights on the performance of different VNS methodologies applied to two diversity problems: the maximum diversity problem and the capacitated dispersion problem.
Publisher: Springer Link

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