RT Journal Article
T1 Solving the manufacturing cell design problem through an autonomous water cycle algorithm
A1 Soto, Ricardo
A1 Crawford, Broderick
A1 Lanza Gutiérrez, José Manuel
A1 Olivares, Rodrigo
A1 Camacho, Pablo
A1 Astorga, Gino
A1 Fuente-Mella, Hanns de la
A1 Paredes, Fernando
A1 Castro, Carlos
AB 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.
PB MDPI
SN 2076-3417
YR 2019
FD 2019-11-06
LK https://hdl.handle.net/10016/32142
UL https://hdl.handle.net/10016/32142
LA eng
NO 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).
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