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An improved chaos immune algorithm based on Hadoop framework to solve job-shop scheduling problem

机译:改进的基于Hadoop框架的混沌免疫算法解决车间作业调度问题

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摘要

Based on the analysis of the inadequate of chaos immune algorithm, an improved chaos immune algorithm for solving job-shop problem is presented. Use combined chaos mapping to increase the diversity of the initial population and Map-Reduce method to reduce the time complexity of algorithm based on Hadoop framework. Through the experiment of antibody population initialization and classic JSSP benchmark, the increase of the performance and effect of the algorithm is verified.
机译:在分析混沌免疫算法不足的基础上,提出了一种解决车间作业问题的改进混沌免疫算法。使用组合混沌映射增加初始种群的多样性,使用Map-Reduce方法降低基于Hadoop框架的算法的时间复杂度。通过抗体种群初始化实验和经典的JSSP基准测试,验证了算法性能和效果的提高。

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