Abstract
The Manufacturing cell design problem focuses on the creation of an optimal distribution of the machinery on a productive plant, through the creation of highly independent cells where the parts of certain products are processed. The main objective is to reduce the movements between this cells, decreasing production times, costs and getting other advantages. To find solutions to this problem, in this paper, the usage of the Flower Pollination Algorithm is proposed, which is one of the many nature-based algorithms, which in this case is inspired in the Pollination of the flowers, and has shown great capacities in the resolution of complex problems. Experimental results are shown, with 90 instances taken from Boctor’s experiments, where the optimum is achieved in all them.
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Acknowledgments
Ricardo Soto is supported by Grant CONICYT/FONDECYT/REGULAR/1160455, Broderick Crawford is supported by Grant CONICYT/FONDECYT/REGULAR/1140897, Rodrigo Olivares is supported by Postgraduate Grant Pontificia Universidad Católica de Valparaíso, Chile (INF-PUCV 2015), and Boris Almonacid is supported by Postgraduate Grant Pontificia Universidad Católica de Valparaíso, Chile (VRIEA-PUCV 2016 and INF-PUCV 2015), by Animal Behavior Society, USA (Developing Nations Research Awards 2016) and by Ph.D (h.c) Sonia Alvarez, Chile.
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Soto, R. et al. (2016). Resolving the Manufacturing Cell Design Problem Using the Flower Pollination Algorithm. In: Sombattheera, C., Stolzenburg, F., Lin, F., Nayak, A. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2016. Lecture Notes in Computer Science(), vol 10053. Springer, Cham. https://doi.org/10.1007/978-3-319-49397-8_16
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