基于改进多种群遗传算法的电力仓库货位分配
Slotting Optimization in Automated Power Warehouse Using Improved Multi-Population Genetic Algorithm
DOI: 10.12677/SG.2018.86068, PDF,   
作者: 宋纪恩, 薛劭节：国网江苏省电力有限公司，江苏 南京；冯曙明：江苏电力信息技术有限公司，江苏 南京
关键词: 电力仓库；货位分配；遗传算法；Power Warehouse； Goods Location Assignment； Genetic Algorithm610
摘要: 针对江苏某电力自动化立体仓库货位优化分配问题，以出入库效率和高层货架稳定性为约束条件，建立了多目标的货位分配优化模型。提出了一种以精英种群为主导的多种群遗传算法用于求解优化模型。仿真实验结果验证了该算法具有更好的收敛性，能够有效提高物料出入库效率和货架的稳定性。
Abstract: Slotting optimization greatly affects the efficiency of automated power warehouse. This paper analyses warehousing efficiency and high-rise shelf stability, then constructs a multi-objective model of slotting optimization. An Improved Multi-Population Genetic Algorithm (IMPGA) which dominated by elite population is proposed to solve the problem. The simulation result shows that IMPGA is practical and effective. It has better convergence and can effectively improve the efficiency of material storage and shelf stability.
文章引用：宋纪恩, 薛劭节, 冯曙明. 基于改进多种群遗传算法的电力仓库货位分配[J]. 智能电网, 2018, 8(6): 610-616. https://doi.org/10.12677/SG.2018.86068

参考文献

[1] Park, B.C., Foley, R.D. and Frazelle, E.H. (2006) Performance of Miniload Systems with Two-Class Storage. European Journal of Operational Research, 170, 144-155.
[Google Scholar] [CrossRef] 
[2] Muppani, V.R. and Adil, G.K. (2008) Efficient Formation of Storage Classes for Warehouse Storage Location Assignment: A Simulated Annealing Approach. Omega, 36, 609-618.
[Google Scholar] [CrossRef] 
[3] 马永杰, 蒋兆远, 杨志民. 基于遗传算法的自动化仓库的动态货位分配[J]. 西南交通大学学报, 2008, 43(3): 421-425.
[4] Li, M., Chen, X. and Liu, C. (2008) Pareto and Niche Genetic Algorithm for Storage Location Assignment Optimization Problem. 3rd International Conference on Innovative Computing Information and Control, 465.
[Google Scholar] [CrossRef] 
[5] 华红艳, 张丹. 基于蚁群算法的自动化立体仓库路径优化[J]. 计算机技术与自动化, 2010, 29(1): 51-54.
[6] 李敬波, 张薇薇. 基于遗传算法的自动化立体库仓库货位优化模型研究[J]. 运作管理, 2016(6): 99-101.
[7] 李鹏飞, 马航. 基于病毒协同遗传算法的自动化立体仓库货位优化模型[J]. 中国管理科学, 2017, 25(5): 70-77.

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