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| Natura: | Artículo científico |
| Lingua: | en |
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Universidad Nacional de Colombia
2013
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| Accesso online: | https://www.redalyc.org/articulo.oa?id=49626817005 |
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| _version_ | 1866572887001923584 |
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| author | Johanna Rodríguez León |
| author_facet | Johanna Rodríguez León |
| contents | Performance comparison between a classic particle swarm optimization and a genetic algorithm in manufacturing cell design Johanna Rodríguez León Jabid Eduardo Quiroga Méndez Nestor Raul Ortiz Pimiento Ingeniería Meta Group Technology heuristic Models Genetic Algorithm Manufacturing cells This article studies the performance of two metaheuristics, the Particle Swarm Optimization (PSO) and the Genetic Algorithm(GA), in the manufacturing cell formation problem of a factory that needs to organize three production cases in an efficient way for four, fiveand six manufacturing cells to produce 30, 40 and 50 different products to be processed in 10, 10 and 20 type machines, respectively. Theprocedure for adjusting the particular parameters of each algorithm is implemented through a Design of Experiments which includes theirown analysis of variance. Both algorithms are implemented in Matlab. The results obtained by each meta heuristic are compared in termsof the cost of the best solution found and the execution time used to find that solution, so that it is possible to establish which methodologyis the most appropriate when solving this optimization problem. 2013 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49626817005 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.178 Vol.80 |
| format | Artículo científico |
| id | redalyc_49626817005 |
| language | en |
| publishDate | 2013 |
| publisher | Universidad Nacional de Colombia |
| spellingShingle | Performance comparison between a classic particle swarm optimization and a genetic algorithm in manufacturing cell design Johanna Rodríguez León Ingeniería Meta Group Technology heuristic Models Genetic Algorithm Manufacturing cells Performance comparison between a classic particle swarm optimization and a genetic algorithm in manufacturing cell design Johanna Rodríguez León Jabid Eduardo Quiroga Méndez Nestor Raul Ortiz Pimiento Ingeniería Meta Group Technology heuristic Models Genetic Algorithm Manufacturing cells This article studies the performance of two metaheuristics, the Particle Swarm Optimization (PSO) and the Genetic Algorithm(GA), in the manufacturing cell formation problem of a factory that needs to organize three production cases in an efficient way for four, fiveand six manufacturing cells to produce 30, 40 and 50 different products to be processed in 10, 10 and 20 type machines, respectively. Theprocedure for adjusting the particular parameters of each algorithm is implemented through a Design of Experiments which includes theirown analysis of variance. Both algorithms are implemented in Matlab. The results obtained by each meta heuristic are compared in termsof the cost of the best solution found and the execution time used to find that solution, so that it is possible to establish which methodologyis the most appropriate when solving this optimization problem. 2013 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49626817005 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.178 Vol.80 |
| title | Performance comparison between a classic particle swarm optimization and a genetic algorithm in manufacturing cell design |
| topic | Ingeniería Meta Group Technology heuristic Models Genetic Algorithm Manufacturing cells |
| url | https://www.redalyc.org/articulo.oa?id=49626817005 |