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The Simulation Optimization for Job-Shop Scheduling Based on Plant Simulation Using Genetic Algorithm

机译:基于遗传算法的工厂仿真的作业型号调度模拟优化

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摘要

The job-shop scheduling problem (JSP), which is one of the best-known machine scheduling problems, is among the hardest combinatorial optimization problems. In this paper, the key technology of building simulation model in Plant Simulation is researched and also the build-in genetic algorithm of optimizing module is used to optimize job-shop scheduling, which can assure the scientific decision. At last, an example is used to illustrate the optimization process of the Job-Shop scheduling problem with Plant Simulation genetic algorithm modules.
机译:作业商店调度问题(JSP)是最着名的机器调度问题之一,是最难的组合优化问题。本文研究了植物仿真中建筑模拟模型的关键技术,以及优化模块的构建遗传算法,用于优化作业商店调度,可以保证科学决策。最后,示例用于说明具有工厂模拟遗传算法模块的作业商店调度问题的优化过程。

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