• 更多栏目

    王旭坪

    • 教授     博士生导师   硕士生导师
    • 主要任职:Deputy Dean,School of Business,Dalian University of Technology
    • 性别:男
    • 毕业院校:大连理工大学
    • 学位:博士
    • 所在单位:系统工程研究所
    • 学科:管理科学与工程
    • 电子邮箱:wxp@dlut.edu.cn

    访问量:

    开通时间:..

    最后更新时间:..

    Multi-objective optimization for delivering perishable products with mixed time windows

    点击次数:

    论文类型:期刊论文

    发表时间:2018-09-01

    发表刊物:ADVANCES IN PRODUCTION ENGINEERING & MANAGEMENT

    收录刊物:SCIE

    卷号:13

    期号:3

    页面范围:321-332

    ISSN号:1854-6250

    关键字:Perishable products distribution; Multi-objective optimization; Mixed time windows; Freshness; Heuristic algorithm; Spatio-temporal distance

    摘要:Perishable products generally have a short shelf life, and the freshness often depends on the postharvest time. The freshness of perishable products can ensure better customer satisfaction. Owing to the deterioration of perishable goods, the complexity of the corresponding vehicle routing problem (VRP) increases, because time delay will lead to serious costs. In this study, we are concerned with not only time-sensitive spoilage rates with mixed time windows, but also the delay costs in delivering perishable products. This study proposes a multi-objective VRP optimization model with mixed time windows and perishability (MO-VRPMTW-P) to minimize the distribution costs and maximize the freshness of perishable products. Then, in view of the fresh products orders space and time characteristics, we propose a heuristic algorithm (ST-VNSGA) composed of a variable neighbourhood search (VNS) method and a genetic algorithm (GA) considering the spatio-temporal (ST) distance to solve the complex multi-objective problem. The solution algorithms are evaluated through a series of experiments. We illustrate the performance and efficiency comparisons of ST-VNSGA with the method without spatio-temporal strategy algorithm and NSGA-II algorithm. It is demonstrated that the proposed ST-VNSGA algorithm can lead to a substantial decrease in the computation time and major improvements in solutions quality, thus revealing the efficiency of considering the spatio-temporal strategy with mixed time windows. (C) 2018 CPE, University of Maribor. All rights reserved.