Abstract
This paper proposes a new hybrid algorithm using ant colony optimization and simulated annealing intelligent approaches to solve a stochastic dynamic facility layout problem in which product demands are normally distributed random variables with known probability density function that changes from period to period in a random manner. Finally, the performance of the proposed algorithm is compared with the simulated annealing and another approach using data taken from the literature.
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© 2012 Springer-Verlag Berlin Heidelberg
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Lee, T.S., Moslemipour, G., Ting, T.O., Rilling, D. (2012). A Novel Hybrid ACO/SA Approach to Solve Stochastic Dynamic Facility Layout Problem (SDFLP). In: Huang, DS., Gupta, P., Zhang, X., Premaratne, P. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2012. Communications in Computer and Information Science, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31837-5_15
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DOI: https://doi.org/10.1007/978-3-642-31837-5_15
Publisher Name: Springer, Berlin, Heidelberg
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