A graph-pair representation and linear programming embedded genetic algorithm for unequal-sized layout of cellular manufacturing systems
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| Publicado en: | Journal of Modelling in Management vol. 20, no. 1 (2025), p. 140-162 |
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Emerald Group Publishing Limited
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| Resumen: | PurposeThis paper aims to deal with intra and inter-cell layout problems in cellular manufacturing systems. The model is organized to minimize the total handling cost, i.e. intra and inter-cell handling costs in a continuous environment.Design/methodology/approachThe research was conducted by developing a mixed integer mathematical model. Due to the complexity and NP-hard nature of the cellular manufacturing layout problem, which mostly originated from binary variables, a “graph-pair” representation is used for every machine set and cells each of which manipulates the relative locations of the machines and cells both in left-right and below-up direction. This approach results in a linear model as the binary variables are eliminated and the relative locations of the machines and cells are determined. Moreover, a genetic algorithm as an efficient meta-heuristic algorithm is embedded in the resulting linear programming model after graph-pair construction.FindingsVarious numerical examples in both small and large sizes are implemented to verify the efficiency of the linear programming embedded genetic algorithm.Originality/valueConsidering the machine and cell layout problem simultaneously within the shop floor under a static environment enabled managers to use this concept to develop the models with high efficiency. |
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| ISSN: | 1746-5664 1746-5672 |
| DOI: | 10.1108/JM2-01-2023-0005 |
| Fuente: | ABI/INFORM Global |