Research on Logistics Distribution Route Based on Multi-objective Sorting Genetic Algorithm

分类 计算机科学 遗传算法 数学优化 路径(计算) 运筹学 生产(经济) 分布(数学) 遗传(遗传算法) 算法 数学 机器学习 数学分析 生物化学 化学 基因 经济 宏观经济学 程序设计语言
作者
Jun Zhao,Hui Xiang,Jinbao Li,Jie Liu,Luyao Guo
出处
期刊:International Journal on Artificial Intelligence Tools [World Scientific]
卷期号:29 (07n08): 2040020-2040020 被引量:11
标识
DOI:10.1142/s0218213020400205
摘要

With the continuous development of society, the social division of labor is further improved, and social production tends to be highly specialized and industrialized. Moreover, enterprise production is increasingly internationalized, and sales are gradually expanding. Therefore, the multi-objective sequencing in logistics distribution is incorporated into the path optimization of the logistics system, and a multi-objective bi-level programming model of time and cost is established. What is more, considering the limitations of the traditional algorithm in solving multi-objective problems, the low-dimensional multi-objective problem is selected, and according to the actual situation, the inheritance strategy of genetic factors is adopted to solve the more targeted rapid dominating sorting genetic problem. Besides, the specific conditions and characteristics of the model determine the encoding method, which is brought into the operation of the cross-mutation law and the interruption of individual populations, so that the building foundation of the model is improved. Based on the further theoretical research on the distribution efficiency of logistics system, the corresponding mathematical model is constructed by using the planning method, and the single cost target is transformed into the time and cost double objective, and the improved fast non dominated sorting genetic algorithm with elite strategy is used to solve the problem, which has certain theoretical innovation. Through simulation, the optimal or near optimal path of distribution vehicles in a certain area is given, which has certain practicality and reference value for the optimization of actual logistics distribution path.

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