TY - JOUR
T1 - A memetic algorithm based on Artificial Bee Colony for optimal synthesis of mechanisms
AU - Vega-Alvarado, Eduardo
AU - Portilla-Flores, E. A.
AU - Munoz-Hernandez, German Ardul
AU - Mezura-Montes, E.
AU - Sepúlveda-Cervantes, G.
AU - Bautista-Camino, P.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - © 2018, Scipedia S.L. All rights reserved. In this paper a novel proposal of a modular hybrid algorithm as a tool for solving real-world engineering problems is presented. A memetic algorithm, MemMABC, is implemented with this approach and applied to solve two case studies of mechanism design, in order to evaluate its efficiency and performance. Because of its modularity, the proposed algorithm is simple and flexible; these features make it quite reusable to be applied on different optimization problems, with a wide scope. The solutions of the optimization problems are also modular, following a scheme of structured programming that includes the use of global variables for configuration, and subroutines for the objective function and the restrictions. Memetic algorithms are a good option to solve hard optimization problems, because of the synergy derived from the combination of their components: a global search population-based metaheuristic and a local refinement method. The quality of simulation results suggests that MemMABC can be successfully applied to solve hard problems in engineering design.
AB - © 2018, Scipedia S.L. All rights reserved. In this paper a novel proposal of a modular hybrid algorithm as a tool for solving real-world engineering problems is presented. A memetic algorithm, MemMABC, is implemented with this approach and applied to solve two case studies of mechanism design, in order to evaluate its efficiency and performance. Because of its modularity, the proposed algorithm is simple and flexible; these features make it quite reusable to be applied on different optimization problems, with a wide scope. The solutions of the optimization problems are also modular, following a scheme of structured programming that includes the use of global variables for configuration, and subroutines for the objective function and the restrictions. Memetic algorithms are a good option to solve hard optimization problems, because of the synergy derived from the combination of their components: a global search population-based metaheuristic and a local refinement method. The quality of simulation results suggests that MemMABC can be successfully applied to solve hard problems in engineering design.
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M3 - Article
SN - 0213-1315
JO - Revista Internacional de Metodos Numericos para Calculo y Diseno en Ingenieria
JF - Revista Internacional de Metodos Numericos para Calculo y Diseno en Ingenieria
ER -