Last-mile distribution planning for fruit-and-vegetable cold chains

车辆路径问题 质量(理念) 冷链 遗传算法 计算机科学 最后一英里(运输) 平面图(考古学) 分布(数学) 产品(数学) 布线(电子设计自动化) 运筹学 英里 数学 工程类 机械工程 计算机网络 数学分析 哲学 物理 几何学 考古 认识论 天文 历史 机器学习
作者
Yu-Hsiang Hsiao,Mu-Chen Chen,Kuan Lu,Cheng Lin Chin
出处
期刊:The International Journal of Logistics Management [Emerald Publishing Limited]
卷期号:29 (3): 862-886 被引量:51
标识
DOI:10.1108/ijlm-01-2017-0002
摘要

Purpose The purpose of this paper is to formulate and solve a last-mile distribution plan problem with concern for the quality of fruits and vegetables in cold chains. Design/methodology/approach The vehicle routing problem with time windows (VRPTW) is extended based on the characteristics of fruit-and-vegetable cold chains. The properties of multiple perishable foods, continuing decline in quality, various requirements for quality levels and optimal temperature settings during vehicle transportation are considered in the VRPTW. The product quality level is defined by the estimation of residual shelf life, which changes with temperature, and is characterized by a stepped decrease during the transportation process as time goes on. A genetic algorithm (GA) is adapted to solve the problem because of its convincing ability to solve VRPTW-related problems. For this purpose, solution encoding, a fitness function and evolution operators are designed to deal with the complicated problem herein. Findings A distribution plan including required fleet size, vehicle routing sequence and what quality level should be shipped out to account for the quality degradation during vehicle transportation is generated. The results indicate that the fulfillment of various requirements of different customers for various fruits and vegetables and quality levels can be ensured with cost considerations. Originality/value This study presents a problem for last-mile delivery of fresh fruits and vegetables which considers multiple practical scenarios not studied previously. A solution algorithm based on a GA is developed to address this problem. The proposed model is easily applied to other types of perishable products.

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