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改进猫群算法在车辆配送路径优化中的应用研究

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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.
Application of Improved Cat Swarm Algorithm in Vehicle Distribution Route Optimization
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.

Fresh Agricultural ProductsDistribution VehiclesRoute PlanningCarbon EmissionsCat Swarm Algorithm

周建军、李林、陈飞

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成都工业职业技术学院,四川 成都 610218

成都师范学院,四川 成都 611130

西华大学,四川 成都 610039

生鲜农产品 配送车辆 路径优化 碳排放量 猫群算法

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

2024

机械设计与制造
辽宁省机械研究院

机械设计与制造

CSTPCD北大核心
影响因子:0.511
ISSN:1001-3997
年,卷(期):2024.399(5)
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