Abstract
This paper proposes an hybrid algorithm for Manufacturing Cell Formation. The two techniques that are combined to address this problem correspond to Particle Swarm Optimization (PSO) and a Data Mining Clustering application. The criterion used to group the machines in cells is based on the minimization of inter-cell movements. A maximum cell size is imposed and the number of cell is parameterizable. Some published exact results have been used as benchmarks to assess the proposed algorithm. The computational results show that the proposed algorithm is able to find the optimal solutions on almost all instances with low variability and stability.
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Duran, O., Rodriguez, N., Consalter, L.A. (2008). Hybridization of PSO and a Discrete Position Update Scheme Techniques for Manufacturing Cell Design. In: Gelbukh, A., Morales, E.F. (eds) MICAI 2008: Advances in Artificial Intelligence. MICAI 2008. Lecture Notes in Computer Science(), vol 5317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88636-5_48
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DOI: https://doi.org/10.1007/978-3-540-88636-5_48
Publisher Name: Springer, Berlin, Heidelberg
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