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首页> 外文期刊>The International Journal of Advanced Manufacturing Technology >Research on immune genetic algorithm for solving the job-shop scheduling problem
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Research on immune genetic algorithm for solving the job-shop scheduling problem

机译：求解作业车间调度问题的免疫遗传算法研究

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摘要

To solve the job-shop scheduling problem more effectively, a method based on a novel scheduling algorithm named immune genetic algorithm (IGA) was proposed. In this study, the framework of IGA was presented via combining the immune theory and the genetic algorithm. The encoding scheme based on processes and the adaptive probabilities of crossover and mutation were adopted, while a modified precedence operation crossover was also proposed to improve the performance of the crossover operator. On the other hand, the “shortest processing time” principle was selected to be the vaccine of IGA and the design method of the immune operator was given at the same time. Finally, the performance of IGA for solving JSP was validated by applying the IGA to Muth and Thompson’s benchmark problems.
机译：为了更有效地解决车间调度问题，提出了一种基于新型调度算法的免疫遗传算法（IGA）。本研究通过结合免疫理论和遗传算法提出了IGA的框架。采用基于过程和交叉与变异的自适应概率的编码方案，同时提出了一种改进的优先运算交叉，以提高交叉算子的性能。另一方面，选择“最短处理时间”的原则作为IGA的疫苗，同时给出了免疫操作者的设计方法。最后，通过将IGA应用于Muth和Thompson的基准测试问题，验证了IGA解决JSP的性能。

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