Hybrid approach to distribution planning reflecting a stochastic supply chain |
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Authors: | Seok Jin Lim Suk Jae Jeong Kyung Sup Kim Myon Woong Park |
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Affiliation: | (1) Department of Industrial Systems Engineering, Yonsei University, 134, Sinchon, Seodaemun, Seoul, South Korea;(2) CAD/CAM Research Center, Korea Institute of Science & Technology (KIST), 39-1, Hawolgok-dong, Seongbuk-gu, Seoul, South Korea |
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Abstract: | Today’s business environment is experiencing as a period of expansion and the globalization. Therefore, a distribution plan
with low cost and high customer satisfaction in supply chain management (SCM) has been widely investigated. The purpose of
this study is to establish optimal distribution planning in the supply chain. In this paper, a hybrid approach involving a
genetic algorithm (GA) and simulation is presented to solve this problem. The GA is employed in order to quickly generate
feasible distribution sequences. Considering uncertain factors such as queuing, breakdowns and repairing time in the supply
chain, the simulation is used to minimize completion time for the distribution plan. The computational results for an example
of a simple supply chain are given and discussed to validate the proposed approach. We obtained a more realistic distribution
plan with optimal completion time by performing the iterative hybrid GA simulation procedure which reflects the stochastic
nature of supply chains. |
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Keywords: | Distribution planning Genetic algorithm Hybrid approach Simulation Supply chain management |
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