Abstract: Intelligent manufacturing technology based on 3D printing has become an important means to promote the transformation and upgrading of spare parts supply chain. In this context, the supply chain coordination problem of scheduled maintenance spare parts is studied under the new mode of “make to order+delivery just in time”. The integrated production and transportation scheduling problem is NP-Hard in manufacturing industry. In this paper, the integrated production and transportation scheduling problem with time windows is studied, the integer programming model is established, the master problem and sub-problem are formulated respectively according to the Dantzig-Wolfe decomposition principle, and an improved branch-and-price algorithm is proposed. In the process of solving the problem, the feasible solution is firstly constructed and the CPLEX optimization software is used to solve the master problem. Secondly, the dominant rules and the acceleration strategies are designed to solve the sub-problem according to the characteristic of the problem, and the non-integer solutions are branched. Finally, the numerical experiment results show that the accuracy of the established model and the improved algorithm are verified. The comparison of CPU time shows that the acceleration strategy can improve the efficiency of the algorithm by about 10 times. By comparing the collaborative decisions between production and transportation with the decisions in actual operation, the scheme designed in this paper can optimize the objective function value by 50.33% on average. This study can not only effectively solve the integrated production and transportation scheduling problem under the new spare parts production mode, but also provide scientific basis for the actual operation decision of enterprises, and realize how to decrease cost and increase efficiency.

Key words: 3D printing; spare parts supply chain management; time windows; integrated production and transportation scheduling; branch-and-price algorithm