Multi-objective Optimization of Cold Chain Logistics Distribution Path Considering Time Tolerance

被引：0
作者：
Wu N. [1 ]
Dai H.-J. [1 ]
Li J.-T. [1 ]
Jiang Q.-H. [2 ]
机构：
[1] School of Transportation Engineering, Dalian Jiaotong University, Liaoning, Dalian
[2] No. 32023, Unit of PLA, Liaoning, Dalian
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2023年 / 23卷 / 02期
关键词：
logistics engineering; multi-objective optimization; simulated plant growth algorithm; time tolerance; vehicle routing optimization;
D O I：
10.16097/j.cnki.1009-6744.2023.02.029
中图分类号：
学科分类号：
摘要：
Aiming at the new characteristics of customers' high requirements on service time under new modes such as "central kitchen & cold chain distribution of food materials", this paper analyzes the cold chain logistics vehicle routing considering time tolerance. According to the time sensitivity of customers, the concept of time tolerance and its quantitative method were proposed, and a multi-objective optimization model of cold chain logistics distribution path was developed with the objectives of maximizing customers' time tolerance and minimizing the cost of cold chain logistics enterprises. The improved multi-objective plant growth simulated algorithm is designed to obtain the Pareto non-inferior solutions with the improvements of generating the initial base point by saving algorithm, adopting mixed random-fixed step size and elite strategy. With the distribution information of Pareto front, the optimal solution selection method was used to select the solution in Pareto's non inferior solution set that can be accepted by both customers and transportation enterprises. An example of a cold chain logistics company was analyzed, and the optimal distribution scheme was obtained to meet the requirements of customers and transportation enterprises. To verify the effectiveness of the model and algorithm, the number of 30, 50 and 100 customers in Solomon's standard calculation examples were selected for further analysis. By comparing with non-dominated sorting genetic algorithm-II algorithm, the superiority of the improved multi-objective simulated plant growth algorithm was verified. The proposed method can provide decision-making basis for cold chain logistics enterprises to make reasonable distribution. © 2023 Science Press. All rights reserved.
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页码：275 / 284
页数：9
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