改进猫群算法在车辆配送路径优化中的应用研究
Application of Improved Cat Swarm Algorithm in Vehicle Distribution Route Optimization
周建军 1李林 2陈飞3
作者信息
- 1. 成都工业职业技术学院,四川 成都 610218
- 2. 成都师范学院,四川 成都 611130
- 3. 西华大学,四川 成都 610039
- 折叠
摘要
为解决在生鲜农产品的车辆配送过程中存在的成本高、碳排放高的问题,以顾客满意度最高和总配送成本最低为目标,构建低碳冷链生鲜农产品的车辆配送路径优化模型.首先,通过多种方法对猫群算法进行优化;然后,用优化的猫群算法对模型进行求解.通过仿真实验对车辆配送路径优化前后效果进行分析,验证了所构建模型的可行性.结果表明,所构建的模型能有效地解决车辆配送的路径优化问题;与传统车辆配送的路径规划方法相比,采用所构建的车辆路径优化模型,车辆配送总路径和碳排放量都有一定程度的改善;车辆总配送路径长度缩短了489.77km、车辆碳排放量降低了21.4%.该方法能有效降低车辆配送过程的总成本和碳排放量,可在一定程度上提高车辆的利用效率和物流企业的市场竞争力.
Abstract
To solve the problems of high cost and high carbon emission in the process of vehicle distribution of fresh agricultural products,the optimization model of vehicle distribution route of low-carbon cold chain fresh agricultural products is established with the goal of the highest customer satisfaction and the lowest total distribution cost.Firstly,the cat colony algorithm is opti-mized by several methods.Then,the constructed model is solved by the optimized cat colony algorithm.The feasibility of the con-structed model is verified by the experimental analysis before and after optimization.Simulations are carried out to analyze the ef-fects of vehicle distribution route optimization before and after,and the feasibility of the proposed method is verified.Compared with a traditional route planning method,by applying the constructed vehicle distribution route optimization model,the total route and carbon emission of vehicle distribution are both decreased to a certain extent.The length of the total route of vehicle dis-tribution is shortened by 489.77km and the carbon emission of vehicle is reduced by 21.4%.The constructed model can effectively reduce the total cost and carbon emissions of vehicle distribution process,and improve the efficiency of vehicle utilization and the market competitiveness of distribution enterprises to a certain extent.
关键词
生鲜农产品/配送车辆/路径优化/碳排放量/猫群算法Key words
Fresh Agricultural Products/Distribution Vehicles/Route Planning/Carbon Emissions/Cat Swarm Algorithm引用本文复制引用
基金项目
2021年中国物流学会、中国物流与采购联合会立项研究课题(2021CSLKT3-147)
出版年
2024
NETL
NSTL
维普
万方数据