微型电脑应用2024,Vol.40Issue(1) :157-160.

基于改进克隆选择算法的电力物资仓储布局规划系统设计

Design of Electric Power Material Storage Layout Planning System Based on Improved Clonal Selection Algorithm

吴璇 马俊明 孙道盛
微型电脑应用2024,Vol.40Issue(1) :157-160.

基于改进克隆选择算法的电力物资仓储布局规划系统设计

Design of Electric Power Material Storage Layout Planning System Based on Improved Clonal Selection Algorithm

吴璇 1马俊明 2孙道盛3
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作者信息

  • 1. 国网甘肃省电力公司,物资事业部,甘肃,兰州 730046
  • 2. 国网甘肃省电力公司综合服务中心,甘肃,兰州 730046
  • 3. 国网兰州供电公司,物资管理部,甘肃,兰州 730070
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摘要

为了实现对电力物资仓储的布局优化,采用Apriori算法构建电力物资仓储优化模型,在克隆选择模型的基础上,加入疫苗接种策略,构建改进克隆选择模型.测试结果显示,在Sphere函数和Ackley函数上,改进克隆选择算法经过400次迭代后趋于收敛,适应度值为10-75和10-17.对F函数进行求解,改进克隆选择算法取得最优解1.03,平均解1.12,平均优化效率8.20%,标准方差0.07,优化效率提升了 14.15%.在对物资进行分类中,改进克隆选择算法准确率分别为94.5%和89.6%.在不同种类的物资出入库中,改进克隆选择算法的最小化出入库时间分别为8.5 s、12.7 s、20.9 s和37.2 s.改进克隆选择算法优化了仓储的布局,提升了电力物资配送的效率.

Abstract

In order to optimize the layout of electric power material storage,the Apriori algorithm is used to build the optimiza-tion model of electric power material storage.Vaccination strategy is introduced to build an improved Clonal selection algo-rithm.The results show that on the Sphere function and Ackley function,the improved Clonal selection algorithm tends to con-verge after 400 iterations,with fitness values of 10-75 and 10-17.By solving the F function,the improved Clonal selection algo-rithm obtains the optimal solution of 1.03,the average solution of 1.12,the average optimization efficiency is 8.20%,the standard deviation is 0.07,and the optimization efficiency increased is 14.15%.In the classification of materials,the accuracy of the improved Clonal selection algorithm is 94.5%and 89.6%.The improved Clonal selection algorithm optimizes the layout of the storage and improves the efficiency of power material distribution.

关键词

仓储布局/Apriori算法/关联分析/克隆选择算法

Key words

warehouse layout/Apriori algorithm/correlation analysis/Clonal selection algorithm

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出版年

2024
微型电脑应用
上海市微型电脑应用学会

微型电脑应用

CSTPCD
影响因子:0.359
ISSN:1007-757X
参考文献量12
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