摘要
针对“中央厨房+食材冷链配送”等新模式下客户对服务时间高要求的特点,本文开展了考虑时间容忍度的冷链物流配送路径研究。首先,依据客户对时间的敏感性,提出时间容忍度概念及其量化方法,构建以客户时间容忍度最大、冷链物流企业成本最小为目标的冷链物流配送路径多目标优化模型,设计以节约算法生成初始基点、采用混合随机-固定步长、精英策略等方式改进多目标模拟植物生长算法求解模型,依据Pareto前沿分布信息,利用最优解选择方法在Pareto非劣解集中选取客户和运输企业均能接受的方案。最后,以某冷链物流公司实例进行分析,得到了满足客户和运输企业要求的最优配送方案。为验证模型和算法的有效性,选取Solomon标准算例中30,50,100位客户做进一步分析,通过与NSGA-II算法对比,验证了改进多目标模拟植物生长算法的优越性,本文的研究思路可为冷链物流企业合理配送提供决策依据。
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.
作者
吴暖
代焕杰
李季涛
蒋奇含
WU Nuan;DAI Huan-jie;LI Ji-tao;JIANG Qi-han(School of Transportation Engineering,Dalian Jiaotong University,Dalian 116028,Liaoning,China;No.32023 Unit of PLA,Dalian 116023,Liaoning,China)
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2023年第2期275-284,共10页
Journal of Transportation Systems Engineering and Information Technology
基金
辽宁省社会科学规划基金青年项目(L20CGL006)。
关键词
物流工程
车辆路径优化
时间容忍度
多目标优化
模拟植物生长算法
logistics engineering
vehicle routing optimization
time tolerance
multi-objective optimization
simulated plant growth algorithm