Algoritmo genético aplicado a la programación en talleres de maquinado//Genetic algorithm applied to scheduling in machine shops

Authors

  • José Eduardo Márquez-Delgado Universidad de Granma. Facultad de Ciencias Técnicas. Granma.
  • Ricardo Lorenzo Ávila-Rondón Universidad de Holguín. Facultad de Ingeniería. Holguín.
  • Miguel Ángel Gómez-Elvira-González Universidad Politécnica de Madrid. Escuela Técnica Superior de Ingenieros Agrónomos. Madrid.
  • Carlos Rafael Herrera-Márquez Empresa de Acumuladores XX Aniversario. Manzanillo, Granma.

Abstract

En este trabajo se utiliza la metaheurística nombrada algoritmo genético, para dos variantes típicas de problemas de planificación presentes en un taller de maquinado de piezas: las variantes flujo general y flujo regular, y se ha seleccionado la minimización del tiempo de finalización de todos los trabajos o
camino máximo, como objetivo a optimizar en un plan de trabajo. Este problema es considerado de difícil solución y es típico de la optimización combinatoria. Los resultados demuestran la calidad de las soluciones encontradas en correspondencia con el tiempo de cómputo empleado, al ser comparados con
problemas clásicos reportados por otros autores. La representación propuesta de cada cromosoma genera el universo completo de soluciones factibles, donde es posible encontrar valores óptimos globales de solución y cumple con las restricciones del problema.

Palabras claves: algoritmo genético, cromosomas, flujo general, flujo regular, planificación, camino máximo.
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Abstract

In this paper we use the metaheuristic named genetic algorithm, for two typical variants of problems of scheduling present in a in a machine shop parts: the variant job shop and flow shop, and the minimization of the time of finalization of all the works has been selected, good known as makespan, as objective to
optimize in a work schedule. This problem is considered to be a difficult solution and is typical in combinatory optimization. The results demonstrate the quality of the solutions found in correspondence with the time of used computation, when being compared with classic problems reported by other authors.
The proposed representation of each chromosome generates the complete universe of feasible solutions, where it is possible to find global good values of solution and it fulfills the restrictions of the problem.

Key words: genetic algorithm, chromosomes, flow shop, job shop, scheduling, makespan.

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How to Cite

1.
Márquez-Delgado JE, Ávila-Rondón RL, Gómez-Elvira-González M Ángel, Herrera-Márquez CR. Algoritmo genético aplicado a la programación en talleres de maquinado//Genetic algorithm applied to scheduling in machine shops. Ing. Mec. [Internet]. 2012 Sep. 1 [cited 2025 Sep. 13];15(3):201-12. Available from: https://ingenieriamecanica.cujae.edu.cu/index.php/revistaim/article/view/430

Issue

Vol. 15 No. 3 (2012): september-december

Section

Original article

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