多车型冷链物流配送车辆的路径优化  

Routing Optimization of Multi-model Cold Chain Vehicle with Travel Time Limit

作　　者：孙国华[1] 屈冉冉 SUN Guohua;QU Ranran(School of Management Science and Engineering,Shan dong University of Finance and Econom ics,Jinan 250014,China;Department of Management and Economics,Tianjin University,Tianjin 300072,China)

机构地区：[1]山东财经大学管理科学与工程学院,山东济南250014 [2]天津大学管理与经济学部,天津300072

出　　处：《山东财经大学学报》2020年第3期111-120,共10页Journal of Shandong University of Finance and Economics

基　　金：国家自然科学基金项目“基于货架空间分配的生鲜农产品供应链协调研究”(71402084)。

摘　　要：针对冷链物流配送系统中存在运输成本和载重量不同的多种车型的情形,通过构建整数规划模型分析了冷链物流配送车辆路径优化问题。由于配送车辆路径优化问题是典型的NP-hard问题,精确算法无法在短时间内求得大规模问题的最优解,因此提出了基于大车优先原则与基于满载优先原则的遗传算法。通过与基于两种原则的C-W节约算法进行对比,发现基于两种原则的遗传算法可以在较短时间内得到平均相对误差更小的解,从而验证了算法的有效性,同时对不同原则适用的情形进行了说明。将算法应用到H冷链物流公司实例中,得出基于两种原则的遗传算法求得的方案所需费用更少,进一步验证了算法的有效性。Aimed at the situation that there are many types of vehicle with different transportation cost and load capacity in the cold chain logistics distribution system,this paper analyzes the routing optimization of cold chain logistics distribution vehicle by constructing integer programming model. Because the distribution vehicle routing optimization is a typical NP-hard problem and the exact algorithm can ’t get the optimal solution of a large-scale problem in a short time,a genetic algorithm is proposed based on the heavy-vehicle priority principle and the fullload priority principle. Through a comparison with C-W saving algorithm based on these two principles,it is found that the genetic algorithm based on the two principles can get a solution with smaller average relative error in a short time,which verifies the effectiveness of this algorithm. And meanwhile the application of different principles is explained. When the algorithm is applied to the example of H cold chain logistics company,the solution achieved by the genetic algorithm based on the two principles needs less cost,which further verifies the effectiveness of the algorithm.

关 键 词：冷链物流 车辆路径优化 多车型 遗传算法 

分 类 号：F252.5[经济管理—国民经济]