系统仿真学报 ›› 2019, Vol. 31 ›› Issue (8): 1582-1590.doi: 10.16182/j.issn1004731x.joss.17-0376

• 仿真建模理论与方法 • 上一篇    下一篇

不确定需求生鲜电商配送路径规划多目标模型

张倩1, 熊英2, 何明珂1,3, 张浩1   

  1. 1. 北京工商大学商学院 北京 100048;
    2. 国网北京市电力公司物资分公司 北京 100054;
    3. 北京物资学院物流学院 北京 101149
  • 收稿日期:2017-08-03 修回日期:2017-11-14 发布日期:2019-12-12
  • 作者简介:张倩(1988-),女,辽宁大连,博士,讲师,研究方向为物流与供应链,交通运输规划管理。
  • 基金资助:
    2018年首都流通业研究基地内设课题(JD-ZD-2018-001),北京市哲学社会科学项目(17GLB013)

Multi-objective Model of Distribution Route Problem for Fresh Electricity Commerce under Uncertain Demand

Zhang Qian1, Xiong Ying2, He Mingke1,3, Zhang Hao1   

  1. 1. Beijing Technology and Business University, Beijing 100048, China;
    2. State Grid Beijing Logistic Supply Company,State Grid Beijing Electric Power Company,Beijing 100054, China;
    3. Beijing Wuzi University, Beijing 101149, China
  • Received:2017-08-03 Revised:2017-11-14 Published:2019-12-12

摘要: 综合考虑配送成本、生鲜产品新鲜度、碳排放和客户需求不确定等因素,建立配送路径规划多目标优化模型。基于鲁棒优化处理不确定问题的方法,针对离散需求隶属于椭球不确定集情况,优化配送路径规划多目标模型,并应用主要目标法和果蝇算法对模型进行求解。算例验证所建模型及算法具有良好的鲁棒性,能有效抑制需求为不确定情况下所带来的扰动。对于完善生鲜电商企业配送路径规划模型和配送网络优化方法提供了重要的理论支持和实践思路。

关键词: 路径规划, 不确定需求, 生鲜电商, 鲁棒优化, 果蝇算法

Abstract: Considering the distribution cost, freshness of fresh products, carbon emissions and customer demand uncertainty and other factors, a multi-objective optimization model of distribution path planning is established. Based on the robust optimization method for dealing with uncertain problems, the multi-objective model of distribution routing planning is optimized for the situation that the discrete demand belongs to the uncertainty set of ellipsoid. The model is solved by using the main target method and fruit fly algorithm. It is proved that the model and algorithm are robust and can effectively suppress the disturbance caused by the uncertainty of the demand. This paper provides an important theoretical basis and practical ideas for improving the distribution route planning model and distribution network optimization method.

Key words: vehicle routing problem, uncertain demand, fresh electronic commerce, robust optimization, fruit fly optimization algorithm

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