A. Ammeri, M. Dammak, H. Chabchoub, Wafik Hachicha, F. Masmoudi
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引用次数: 3
摘要
本文提出了一种结合仿真和遗传算法的优化模型，用于解决订单制造(MTO)供应链中的批量问题。利用ARENA软件建立仿真模型。GA模型使用VBA (Visual Basic for Application)语言实现，以保证ARENA软件与Ms Excel之间的交互。遗传算法和仿真模型随着时间的推移与交互并行运行。本案例研究的目标是确定每种制造产品类型的固定最佳批量，以确保每种成品的订单平均流程时间目标。与采用全局搜索方法的OptQuest软件进行了对比，验证了该方法的有效性和有效性。
A simulation optimization approach-based genetic algorithm for lot sizing problem in a MTO sector
In this paper, a combined simulation and Genetic Algorithm (GA) optimization model is developed to solve the Lot Sizing Problem (LSP) in a Make to Order (MTO) supply chain. The simulation model is performed using ARENA software. GA model is implemented using Visual Basic for Application (VBA) language, because it ensures exchanges between ARENA software and Ms Excel. The GA and simulation models operate in parallel over time with interactions. The case study's objective is to determine a fixed optimal lot size for each manufactured product type that will ensure order mean flow time target for each finished product. The comparative results with OptQuest software, which is used a global search method, to illustrate the efficiency and effectiveness of the proposed approach.
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