基于改进遗传算法的自动化仓库仓储分配策略研究

Wen Shi, Yue-Xia Tian, Song Wang, ChunWen Liu, Lei Yang, PiChao Zheng
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引用次数: 0

摘要

本文主要研究自动化立体仓库的最优仓储配置策略。从货物流通效率、货架稳定性、货物分拣储存三个方面建立目标数学模型,采用多目标降维方法,将多个目标转化为单个目标。该算法以遗传算法为基础,引入小生境技术和模拟退火算法进行改进,并采用自适应交叉变异算子在迭代后期保护优秀个体。最后,以连云港某氨纶公司的自动化仓库为例进行实验分析。结果表明,与常规遗传算法相比,改进遗传算法收敛速度更快,解集质量更好,对存储分配更有效。
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Research on Storage Allocation Strategy of Automated Warehouse Based on Improved Genetic Algorithm
This article is mainly to study the optimal storage allocation strategy of automated three-dimensional warehouse. A target mathematical model will be established from three aspects: goods circulation efficiency, shelf stability, and sorting and storage of goods, and a multi-target dimensionality reduction method will be used to convert multiple targets into single targets. The algorithm is based on genetic algorithm, introduces niche technology and simulated annealing algorithm for improvement, and adopts an adaptive cross-mutation operator to protect outstanding individuals in the later stage of the iteration. Finally, take the automated warehouse of a spandex company in Lianyungang as an example for experimental analysis. The results show that, compared with the regular genetic algorithm, the improved one converges faster, the solution set quality is better, and it is more effective for the storage allocation.
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