Presenting an Integrated Model for Production Planning and Preventive Maintenance Scheduling Considering Uncertainty of Parameters and Disruption of Facilities

The scheduling of parallel machines and preventive maintenance is one of the key issues in the field of production processes, and has always been a topic of interest for researchers. This research aims to design an integrated model for scheduling and preventive maintenance for parallel machines considering the probability of disruption in facilities and uncertainty in parameters of the model. In this regard, a mathematical scheduling model has been proposed with two objective functions of minimizing the weighted completion time of products and maximizing the reliability of the production line. The NP-hard nature of the studied problem from a computational perspective, meta-heuristic algorithms such as NSGA-II and MOPSO were utilized to solve numerical problems in medium and large scales. Therefore, numerical problems were designed in different size and solved by the proposed algorithms. The results showed that the NSGA-II compared to the MOPSO algorithm provide better solutions. However, MOPSO has better efficiency than NSGA-II in term of computation time, this superiority is not considerable and it can not be considered as a definitive basis for comparing two algorithms.