基于混合差分进化算法的作业车间调度问题

Wang Wei-ling, Yin Jing
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引用次数: 8

摘要

研究了具有放行日期和到期日的作业车间问题,其目标是使总加权延迟最小化。在析取图模型上,将差分进化算法与改进的关键路径算法相结合,提出了一种混合差分进化算法(HDE)。首先,提出了一种作业分组顺序规则,将DE中个体(实向量)的连续值转化为作业排列;其次,在基于DE的全局搜索之后,将改进的关键路径算法用于局部搜索,以提高局部搜索能力;在文献实例上进行的大量计算实验表明了所提出的HDE算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A hybrid differential evolution algorithm for job shop scheduling problem to minimize the total weighted tardiness
This paper considers the job-shop problem with release dates and due dates, with the objective of minimizing the total weighted tardiness. A hybrid DE (HDE) is presented by combining differential evolution algorithm with the improved critical path algorithm on a disjunctive graph model. Firstly, a job-grouping-order (JPO) rule is presented to convert the continuous values of individuals (real vectors) in DE to job permutations. Secondly, after the global exploration based on DE, the improved critical path algorithm are used in a local search in order to improve the local search ability. An extensive computational experiment carried out on instances of the literature shows the performance of the proposed HDE algorithm.
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