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Based on genetic algorithm for Job Shop scheduling problem
基于遗传算法的Job Shop调度问题研究

Keywords: 车间调度问题,遗传算法,资源分配,总延迟时间

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Abstract:

This study addressed a job scheduling and resource allocation problem with distinct release dates and due dates to minimize total tardiness in parallel work centers with a multi-processor environment. To solve the problem, this study also proposed a hybrid genetic algorithm (HGA) with release and due dates based decomposition heuristic. Experimental results show that the percentage deviations between the HGA and Lingo are smaller than 15%, and the HGA has smaller variance than the GA. This study proposed a decision-supporting model, which integrated simulation, genetic algorithms and decision support tools, for solving the JSRA problem by practical perspective.

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