Approximate Approach to Deal with the Uncertainty in Integrated Production Scheduling and Maintenance Planning

This paper deals with the integration problem between production scheduling and maintenance planning in a single machine, where the impact of failure uncertainty is considered. The objective is to minimize the weighted sum of quality robustness and solution robustness, which is determined by the jobs’ sequence, preventive maintenances’ position and buffer time in the schedule. Then, a three-stage algorithm is devised to solve the problem, where the gradient descent algorithm based on an effective surrogate measure is developed in the second stage. The numerical experiments show that the deviation of the approximate approach is very small, as compared with the exact solution obtained by CPLEX. The balance between quality robustness and solution robustness and the distribution of buffer time in different scenarios are shown in a case study. It validates the necessity and effectiveness of the consideration of robustness in the industrial practice.