Abstract: In the context of integrating intelligent manufacturing and Just-In-Time delivery, the integrated production and transportation scheduling problem of spare parts is a hot topic in China. The reason is that the response speed of spare parts supply chain has become a key factor for spare parts manufacturing enterprises to win customers. In order to improve the satisfaction of customers and shorten the time from placing an order by customer to the delivery of the order, this paper studies an integrated production and transportation scheduling problem aiming at minimizing the delivery time of all customers. An integer programming model and a set-covering modelareproposed respectively. The property of the optimal solution is developed and an improved branch-and-price algorithmisproposed to solve the problem instances to optimality. The formulation and algorithm are verified by comparing the results of the small-scale problem instances with CPLEX. The experimental results based on multiple problem instances show that the proposed formulation and algorithm can effectively improve the operation efficiency of spare parts supply chain in intelligent manufacturing environment.

Key words: intelligent manufacturing, Just-In-Time delivery, integrated production and transportation scheduling, set-covering formulation, branch-and-price algorithm

摘要： 智能制造和即时配送环境下的备件生产与运输协同调度问题是目前国内研究的一大热点,这是因为备件供应链响应速度已成为当前备件制造企业赢得客户的关键因素。为了提高客户满意度,尽可能缩短从客户下达定制化生产订单到订单配送完成的时间,本文建立了以所有客户总等待时间最短为目标的混合整数规划模型和集合覆盖模型,推导了最优解性质,并设计改进的分支定价算法求得最优解。通过将小规模算例结果与CPLEX进行对比,验证了模型和算法的有效性。多组算例测试结果表明,所提出的模型和算法可以有效提升智能制造环境下的备件供应链运作效率。

关键词: 智能制造, 即时配送, 生产与运输协同调度, 集合覆盖模型, 分支定价算法