Abstract
Distribution decisions play an important role in the strategic planning of supply chain management. In order to use the most proper strategic decisions in a supply chain, decision makers should focus on the identification and management of the sources of uncertainties in the supply chain process. In this paper these conditions in a multi-period problem with demands changed over the planning horizon is considered. We develop a non-linear mixed-integer model and propose an efficient heuristic genetic based algorithm which finds the optimal facility locations/allocation, relocation times and the total cost, for the whole supply chain. To explore the viability and efficiency of the proposed model and the solution approach, various computational experiments are performed based on the real size case problems.
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References
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© 2010 Springer-Verlag Berlin Heidelberg
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Nasiri, G.R., Davoudpour, H., Movahedi, Y. (2010). A Genetic Algorithm Approach for the Multi-commodity, Multi-period Distribution Planning in a Supply Chain Network Design. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2010. Lecture Notes in Computer Science, vol 6466. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17563-3_58
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DOI: https://doi.org/10.1007/978-3-642-17563-3_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17562-6
Online ISBN: 978-3-642-17563-3
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