摘要
面对竞争日益激烈的农产品电商市场,企业需要在鲜活农产品配送领域寻找更优秀的配送规划方法。为此,此次研究建立了考虑时间窗约束的鲜活农产品配送模型,并利用自组织映射算法(Self-organization Mapping net,SOM)改进了遗传算法(Genetic Algorithm,GA)的个体更新策略,得到了SOM-GA算法用于优化问题求解。实验结果显示,该算法在迭代70次后即可收敛,收敛性能较好。其求解规划的路线最短为60.34km,所需总成本为63万元,配送途中车辆总等待时间为2.13min,顾客对配送的满意度为97.26%。与人工计算的方案相比,该算法的求解方案成本稍低。与其他方法相比,该算法求解的总成本、最短路线长度、资源成本和时间窗成本综合最小。可见,本研究设计的基于改进遗传算法的物流规划求解方法有较好的路线规划性能,可以在满足顾客对鲜活农产品配送的时间要求之外,为企业最大程度地降本增效。
Facing the increasingly competitive agricultural products e-commerce market,companies need to find a better distribution planning method in the field of fresh and live agricultural products distribution.To this end,this study establishes a fresh produce distribution model considering time window constraints,and improves the individual update strategy of genetic algorithm by using Self-organization Mapping net(SOM)to obtain the SOM-GA algorithm for optimization problem solving.The experimental results show that the algorithm converges after 70 iterations and has good convergence performance.The shortest route planned by its solution is 60.34 km,the total cost required is 630,000yuan,the total vehicle waiting time during the delivery is 2.13 minutes,and the customer satisfaction of the delivery is 97.26%.Compared with the manually calculated solution,the algorithm has a slightly lower cost to solve the solution.The algorithm has the smallest combined total cost,shortest route length,resource cost and time window cost for solving compared to other methods.It can be seen that the logistics planning solution method based on improved genetic algorithm designed in this study has better route planning performance and can maximize the cost reduction and efficiency for the enterprise in addition to meeting the time requirements of customers for fresh produce distribution.
作者
史健
SHI Jian(Anhui Technical College of Water Resources and Hydroelectric Power,Hefei 231603,China)
出处
《佳木斯大学学报（自然科学版）》
CAS
2023年第3期151-155,共5页
Journal of Jiamusi University：Natural Science Edition
基金
安徽省高等学校质量工程产教融合实训基地项目(2021cjrh016)。
关键词
改进遗传算法
SOM
鲜活农产品
物流配送
路线规划
improved genetic algorithm
SOM
fresh and live agricultural products
logistics and distribution
route planning
