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多行程多交货期的成品油配送优化
引用本文:高海龙,谢勇,马吉祥,张波.多行程多交货期的成品油配送优化[J].控制与决策,2022,37(10):2714-2722.
作者姓名:高海龙  谢勇  马吉祥  张波
作者单位:华中科技大学 人工智能与自动化学院,武汉 430074;上海幸宜信息科技有限公司,上海 200439
基金项目:国家自然科学基金项目(71771096);国家自然科学基金创新群体项目(71821001).
摘    要:研究多行程多交货期的成品油配送优化问题,已知油库使用带运输时间窗的多舱车辆配送各加油站的多个订单, 每个加油站具有各自的优先级,且加油站的各个订单带有交货期.综合考虑客户优先级、订单交货期和车辆运输时间窗等因素,以配送收益最大化为目标,建立多行程多交货期的成品油配送优化模型,并设计带交货期移除算子的改进变邻域搜索算法进行求解.基于前向插入启发式算法构造初始解,设计基于订单交货期的邻域扰动算子和基于单位时间收益最大化的贪婪策略,以增强算法的局部寻优能力,并提出基于逆序访问的后期优化策略,从而在保证解的质量情况下加快算法收敛速度.通过不同规模下的仿真实验验证了所提出模型和算法在最大化配送收益的同时,能够有效地提高配送及时性.

关 键 词:多行程  订单交货期  运输时间窗  客户优先级  成品油配送  变邻域搜索算法

Optimization of refined oil distribution with multiple trips and multiple due time
GAO Hai-long,XIE Yong,MA Ji-xiang,ZHANG Bo.Optimization of refined oil distribution with multiple trips and multiple due time[J].Control and Decision,2022,37(10):2714-2722.
Authors:GAO Hai-long  XIE Yong  MA Ji-xiang  ZHANG Bo
Affiliation:School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan 430074,China; Shanghai Xingyi Information Technology Co.Ltd.,Shanghai 200439,China
Abstract:This paper studies the optimization problem of refined oil distribution with multiple trips and multiple due time. Oil depots use multi-cabin vehicles with transportation time windows to distribute multiple orders from each gas station. Each gas station has its own priority, and each order of one gas station has a due time. Comprehensively considering factors including customer priority, order due time, and vehicle transportation time window, with the goal of maximizing distribution revenue, a distribution optimization model of refined oil with multiple trips and multiple due time is established. The improved variable neighborhood search algorithm with the due time removal operator is used to solve the problem. An initial solution based on pushing forward insertion heuristic is constructed. The neighborhood perturbation operator is designed according to the order due time, and a greedy strategy based on the maximum return per unit time is designed to enhance the local optimization ability of the algorithm. A later optimization strategy based on reverse order access is proposed to speed up the convergence speed while ensuring the quality of the solution. The effectiveness of the algorithm is verified by simulation experiments under different scales. The experimental results show that the proposed model and algorithm can not only maximize the distribution revenue, but also effectively improve timeliness of delivery.
Keywords:
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