Lim, SJ Jeong, SJ Kim, KS Park, MW 2024-01-21T03:36:07Z 2024-01-21T03:36:07Z 2021-09-02 2006-03 0268-3768 https://pubs.kist.re.kr/handle/201004/135726 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. English SPRINGER LONDON LTD SIMULATION METHODOLOGY ALGORITHM NETWORK MODELS Hybrid approach to distribution planning reflecting a stochastic supply chain Article 10.1007/s00170-004-2398-7 1 INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, v.28, no.5-6, pp.618 - 625 INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 28 5-6 618 625 scie scopus 000236497300025 2-s2.0-33645504623 Automation & Control Systems Engineering, Manufacturing Automation & Control Systems Engineering Article SIMULATION METHODOLOGY ALGORITHM NETWORK MODELS distribution planning genetic algorithm hybrid approach simulation supply chain management