摘要
农产品物流配送过程中时间和成本最小化是一个关键的问题。研究在分析农产品特点和用户需求的前提下构建农产品物流配送路径模型,并利用改进遗传算法对该模型进行求解。实验表明遗传算法和改进遗传算法的最优解分别为16087.9元和15129.6元,最优配送路径分别有9条和10条。改进遗传算法的最优目标函数值为最具有优势。改进遗传算法在求解农产品物流配送模型中具有合理性和有效性,能获取最佳路径和最优目标值。
Minimization of time and cost in the process of agricultural product logistics distribution is a key issue.On the premise of analyzing the characteristics of agricultural products and the needs of users,this paper constructs the logistics distribution path model of agricultural products,and uses improved genetic algorithm to solve the model.The experimental results show that the optimal solutions of genetic algorithm and improved genetic algorithm are 16087.9 yuan and 15129.6 yuan respectively,and the optimal distribution paths are 9 and 10,respectively.The optimal objective function value of the improved genetic algorithm is the most advantageous.The improved genetic algorithm is reasonable and effective in solving the agricultural product logistics distribution model,and can obtain the best path and the best target value.
作者
汪晔
WANG Ye(Anhui Business College of Vocational Technology,Wuhu Anhui 241000,China)
出处
《佳木斯大学学报（自然科学版）》
CAS
2023年第2期154-157,共4页
Journal of Jiamusi University：Natural Science Edition
基金
安徽省自然科学重点项目(KJ2020A1078)。
关键词
遗传算法
农产品
物流配送
时间窗
genetic algorithm
agriculture products
logistics distribution
time window
作者简介
汪晔(1983-),男,安徽芜湖人,副教授,硕士,研究方向:物流管理。
