文献类型：期刊文献

中文题名：基于双模式更新五行环算法的多目标冷链配送

英文题名：Multi-Objective Cold Chain Distribution Based on Dual-Mode Updated Five-Element Cycle Algorithm

作者：任静[1];项月[1];刘漫丹[1]

机构：[1]华东理工大学信息科学与工程学院,上海200237

年份：2023

卷号：49

期号：2

起止页码：236

中文期刊名：华东理工大学学报（自然科学版）

外文期刊名：Journal of East China University of Science and Technology

收录：Scopus;北大核心:【北大核心2020】；CSCD:【CSCD_E2023_2024】；

语种：中文

中文关键词：双模式;多目标优化;冷链物流;路径优化;FECO算法

外文关键词：dual mode;multi-objective optimization;cold chain logistics;route optimization;FECO algorithm

摘要：针对生产运输中广泛存在的冷链配送问题,建立了以配送成本最小化和顾客满意度最大化为目标函数的多目标冷链物流优化模型。基于五行环优化(FECO)算法,提出了双模式更新个体的五行环优化算法(FECO-DMUI),并对多目标冷链物流模型进行求解。将FECODMUI算法与FECO算法、NSGA-II算法、鲸鱼优化算法和灰狼优化算法进行比较,结果验证了本文模型和算法的有效性,同时验证了FECO-DMUI算法在多目标冷链配送问题中能更加高效地获得路径优化的最优解集。
With the development of the logistics industry,cold chain logistics,as an important branch of the logistics industry,have been receiving more and more attention.The waste of resources in cold chain logistics and distribution is a problem that cannot be underestimated.It is a promising strategy for reducing resource waste via solving the multi-objective optimization model to provide an effective distribution plan.To this end,this paper establishes a multi-objective cold chain logistics optimization model with minimizing distribution costs and maximizing customer satisfaction as the objective function.Customer satisfaction is reflected via the relationship between the delivery vehicle’s arrival time at the customer’s point and the customer’s specific time window.Delivery costs are composed of transportation costs,cargo damage costs,cooling costs,and time penalty costs.We propose a five-element cycle optimization(FECO)algorithm with dual-mode updating individuals(FECODMUI)to solve the multi-objective cold chain logistics optimization model.By comparing with FECO algorithm,NSGA-II,whale optimization algorithm and gray wolf optimization algorithm,the proposed model and FECODMUI algorithm is effectively verified through specific examples.Meanwhile,it is shown that FECO-DMUI algorithm can obtain the optimal solution set of path optimization more efficiently in the multi-objective cold chain distribution problem.