摘要
末端物流配送环节是参与主体最为复杂的环节,其配送成本与配送效率与物流公司和客户息息相关。文章针对多配送中心的物流配送情况,以配送成本最低为目标,建立物流配送数学模型,之后通过设计深度强化学习算法,建立学习环境,对案例进行求解,得到配送车辆的行驶路径,结果表明以深度强化学习求解车辆路径问题,具有较高的可行性。
The terminal logistics distribution process is the most complex one for the participating parties,and its distribution cost and efficiency are closely related to the logistics company and customers.This paper focuses on the logistics distribution situation of multiple distribution centers,with the goal of minimizing distribution costs,and establishes a logistics distribution mathematical model.Then,by designing deep reinforcement learning algorithms,a learning environment is established,and the case is solved to obtain the driving path of distribution vehicles.The results show that using deep reinforcement learning to solve the vehicle routing problem is highly feasible.
作者
王扬
张文浩
WANG Yang;ZHANG Wen-hao(Beijing University of Technology,Beijing 100124)
出处
《供应链管理》
2024年第4期78-87,共10页
SUPPLY CHAIN MANAGEMENT
关键词
车辆路径问题
末端物流配送
深度强化学习
vehicle routing problem
terminal logistics distribution
deep reinforcement learning
