Abstract
Manufacturing Cell Design is a problem that consist in distributing machines in cells, in such a way productivity is improved. The idea is that a product, build up by using different parts, has the least amount of travel on its manufacturing process. To solve the MCDP we use the Bat Algorithm, a metaheuristic inspired by a feature of the microbats, the echolocation. This feature allows an automatic exploration and exploitation balance, by controlling the rate of volume and emission pulses during the search. Our approach has been tested by using a well-known set of benchmark instances, reaching optimal values for most of them.
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Acknowledgements
Ricardo Soto is supported by grant CONICYT/FONDECYT/REGULAR/1160455, Broderick Crawford is supported by grant CONICYT/FONDECYT/REGULAR/1140897, Victor Reyes is supported by grant INF-PUCV 2015, and Ignacio Araya is supported by grant CONICYT/FONDECYT/INICIACION/11121366.
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Soto, R. et al. (2016). Solving Manufacturing Cell Design Problems by Using a Bat Algorithm Approach. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2016. Lecture Notes in Computer Science(), vol 9712. Springer, Cham. https://doi.org/10.1007/978-3-319-41000-5_18
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DOI: https://doi.org/10.1007/978-3-319-41000-5_18
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