Solving the manufacturing cell design problem through an autonomous water cycle algorithm

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dc.contributor.author Soto, Ricardo
dc.contributor.author Crawford, Broderick
dc.contributor.author Lanza Gutiérrez, José Manuel
dc.contributor.author Olivares, Rodrigo
dc.contributor.author Camacho, Pablo
dc.contributor.author Astorga, Gino
dc.contributor.author Fuente-Mella, Hanns de la
dc.contributor.author Paredes, Fernando
dc.contributor.author Castro, Carlos
dc.date.accessioned 2021-03-15T12:44:24Z
dc.date.available 2021-03-15T12:44:24Z
dc.date.issued 2019-11-06
dc.identifier.bibliographicCitation Soto, R., Crawford, B., Lanza-Gutierrez, J. M., Olivares, R., Camacho, P., Astorga, G., Fuente-Mella de la, H., Paredes, F., Castro, C. (2019). Solving the Manufacturing Cell Design Problem through an Autonomous Water Cycle Algorithm. Applied Sciences, 9(22), 4736
dc.identifier.issn 2076-3417
dc.identifier.uri http://hdl.handle.net/10016/32142
dc.description.abstract Metaheuristics are multi-purpose problem solvers devoted to particularly tackle large instances of complex optimization problems. However, in spite of the relevance of metaheuristics in the optimization world, their proper design and implementation to reach optimal solutions isnot a simple task. Metaheuristics require an initial parameter configuration, which is dramatically relevant for the efficient exploration and exploitation of the search space, and therefore to the effective finding of high-quality solutions. In this paper, the authors propose a variation of the water cycle inspired metaheuristic capable of automatically adjusting its parameter by using the autonomous search paradigm. The goal of our proposal is to explore and to exploit promising regions of the search space to rapidly converge to optimal solutions. To validate the proposal, we tested 160 instances of the manufacturing cell design problem, which is a relevant problem for the industry, whose objective is to minimize the number of movements and exchanges of parts between organizational elements called cells. As a result of the experimental analysis, the authors checked that the proposal performs similarly to the default approach, but without being specifically configured for solving the problem.
dc.description.sponsorship Ricardo Soto is supported by Grant CONICYT/FONDECYT/REGULAR/1190129. Broderick Crawford is supported by Grant CONICYT/FONDECYT/REGULAR/1171243. Rodrigo Olivares is supported by Postgraduate Grant Pontificia Universidad Católica de Valparaíso (INF-PUCV 2015).
dc.format.extent 22
dc.language.iso eng
dc.publisher MDPI
dc.rights © 2019 by the authors
dc.rights Atribución 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by/3.0/es/
dc.subject.other Metaheuristic
dc.subject.other Water cycle algorithm
dc.subject.other Autonomous search
dc.subject.other Manufacturing cell design problem
dc.title Solving the manufacturing cell design problem through an autonomous water cycle algorithm
dc.type article
dc.subject.eciencia Electrónica
dc.identifier.doi https://doi.org/10.3390/app9224736
dc.rights.accessRights openAccess
dc.type.version publishedVersion
dc.identifier.publicationfirstpage 1
dc.identifier.publicationissue 22 (4736)
dc.identifier.publicationlastpage 22
dc.identifier.publicationtitle Applied Sciences
dc.identifier.publicationvolume 9
dc.identifier.uxxi AR/0000024426
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