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Multi-start methods for the capacitated clustering problem

Martinez-Gavara, Anna; Campos, Vicente; Landa-Silva, Dario; Marti, Rafael

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Authors

Anna Martinez-Gavara

Vicente Campos

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DARIO LANDA SILVA DARIO.LANDASILVA@NOTTINGHAM.AC.UK
Professor of Computational Optimisation

Rafael Marti



Abstract

In this work, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRASP) and Iterated Greedy methodologies to the Capacitated Clustering Problem (CCP). In particular, we focus on the effect of the balance between randomization and greediness on the performance of these multi-start heuristic search methods when solving this NP-hard problem. The former is a memory-less approach that constructs independent solutions, while the latter is a memory-based method that constructs linked solutions, obtained by partially rebuilding previous ones. Both are based on the combination of greediness and randomization in the constructive process, and coupled with a subsequent local search phase.

Citation

Martinez-Gavara, A., Campos, V., Landa-Silva, D., & Marti, R. (2017). Multi-start methods for the capacitated clustering problem. In Metaheuristics: Proceeding of the MIC and MAEB 2017 Conferences

Conference Name 12th Metaheuristics International Conference (MIC 2017)
Conference Location Barcelona, Spain
Start Date Jul 4, 2017
End Date Jul 7, 2017
Acceptance Date Mar 27, 2017
Publication Date Jul 4, 2017
Deposit Date Aug 11, 2017
Publicly Available Date Aug 11, 2017
Peer Reviewed Peer Reviewed
Book Title Metaheuristics: Proceeding of the MIC and MAEB 2017 Conferences
ISBN 9788469742751
Public URL https://nottingham-repository.worktribe.com/output/871387
Related Public URLs http://mic2017.upf.edu/
Additional Information Published in: Metaheuristics: Proceeding of the
MIC and MAEB 2017 Conferences, 4-7 July 2017, Barcelona, Spain, p. 926-928. Universitat Pompeu Fabra. ISBN: 978-84-697-4275-1.

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