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Adaptive and Multilevel Metaheuristics Read chapter Read first chapter

2018 | OriginalPaper | Chapter

12. Variable Neighborhood Descent

Authors : Abraham Duarte, Jesús Sánchez-Oro, Nenad Mladenović, Raca Todosijević

Published in: Handbook of Heuristics

Publisher: Springer International Publishing

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Abstract

Local search heuristic that explores several neighborhood structures in a deterministic way is called variable neighborhood descent (VND). Its success is based on the simple fact that different neighborhood structures do not usually have the same local minimum. Thus, the local optima trap problem may be resolved by deterministic change of neighborhoods. VND may be seen as a local search routine and therefore could be used within other metaheuristics. In this chapter, we discuss typical problems that arise in developing VND heuristic: what neighborhood structures could be used, what would be their order, what rule of their change during the search would be used, etc. Comparative analysis of usual sequential VND variants is performed in solving traveling salesman problem.

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previous chapter Theory of Local Search
next chapter Ant Colony Optimization: A Component-Wise Overview
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Metadata
Title
Variable Neighborhood Descent
Authors
Abraham Duarte
Jesús Sánchez-Oro
Nenad Mladenović
Raca Todosijević
Copyright Year
2018
Book
Handbook of Heuristics

Print ISBN: 978-3-319-07123-7

Electronic ISBN: 978-3-319-07124-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-07124-4_9

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