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上海电力的大学学报:2020,36(3):265-270
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化验室资源调度优化的改进型克隆选择算法
(上海电力大学 自动化工程学院)
An Improved Clonal Immune Algorithm for Laboratory Resource Scheduling
(School of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)
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投稿时间:2019-12-13    
中文摘要: 为了提升化验室处理化验单能力,实现资源调度优化,建立了化验室调度模型,引入了克隆选择算子、自适应变异算子以及多种群协同进化思想,提出了改进型克隆选择算法,并运用该算法对化验室处理化验单进行了调度优化。将改进型克隆选择算法与多种类型算法进行对比,结果显示,改进型克隆选择算法能有效改善早熟收敛问题,提高搜索效率,获得最优分配方案,适用于化验室化验单调度问题,满足实际要求。
Abstract:In order to improve the laboratory order processing ability and realize resource scheduling optimization,a laboratory scheduling model was established.An improved clonal immune algorithm was proposed by introducing clonal selection operator,adaptive mutation operator and multi-population evolution.The algorithm was used to optimize laboratory processing laboratory orders.The experimental results show that the improved clonal selection algorithm can effectively improve the premature convergence problem,improve the search efficiency and obtain the optimal allocation scheme.It is suitable for laboratory scheduling and meets the practical requirements.
文章编号:20203011     中图分类号:TP301.6    文献标志码:
基金项目:上海市科学技术委员会地方能力建设项目(18020500900)。
引用文本:
顾伟伟,张栋良.化验室资源调度优化的改进型克隆选择算法[J].上海电力大学学报,2020,36(3):265-270.
GU Weiwei,ZHANG Dongliang.An Improved Clonal Immune Algorithm for Laboratory Resource Scheduling[J].Journal of Shanghai University of Electric Power,2020,36(3):265-270.