摘要
越库配送网络具有低存储、高效率等特性,其实施的关键在于内部的协同到库、分拣和外部的车辆配送路径的有效融合。与此同时,配送环境的复杂性增加配送时间的不确定性,使物流服务接受者感知到不同的服务价值差异。本文结合前景理论,构造客户时间窗服务价值函数,并建立寻求时间窗服务价值最大和总成本最小的越库物流配送多目标优化模型。根据优化模型的特征,设计了禁忌搜索算法和局部搜索算法相结合的混合算法,通过算例仿真,验证了优化模型和求解算法是可行和有效的。
The cross-docking distribution network has the characteristics of low storage and high efficiency, and the key to its implementation is the effective integration of internal coordination, sorting and external vehicle routing. Meanwhile, the complexity of the distribution environment increases the uncertainty of delivery time, making logistics service recipients perceive different service value. Combined with the prospect theory, the customer time window service value function is given. And a multi-objective optimization model for cross-docking logistics distribution aimed to find the lowest total cost and the largest value of time window service is proposed. Then, a hybrid algorithm combining tabu search algorithm and local search algorithm is designed to find the optimal solution. Finally, the simulation of the example verify the feasibility and effectiveness of the model and the algorithm.
作者
刘虹
林楚玥
LIU HONG;LIN CHUYUE(School of Economic and Management,Fuzhou University,Fuzhou,350100,China)
基金
福建省自然科学基金项目“智慧物流配送网络动态集成与自适应优化模型及其算法”(2014J05082)
关键词
越库配送
车辆路径
前景理论
多目标优化
禁忌搜索算法
cross-docking
vehicle routing
prospect theory
multi-objectives
tabu search algorithm
