abstract
- Nowadays, process automation and the requirement for simultaneous decision making in supply chain processes have driven the evolution of production planning and scheduling models. One of the problems best known for its complexity and real-industry use is the Flexible Job Shop Problem. The difficulty of planning preventive maintenance and fitting it in the production schedule in the optimal way requires the creation of mathematical models capable of describing the problem and solving it. Machine setup times make the problem more realistic, given that setup times are in fact different from the time taken by the machines to process the jobs. In this paper, an Integer Linear Programming model is presented to describe the problem and solve short instances while a Variable Neighborhood Descent algorithm is used to solve large instances. To test the performance of this model, some instances are created using random numbers. The results showed that the mathematical model finds the optimal solution for the majority of the instances and the results of the large instances are reported to be used as references for future work. © © 2025 The Authors.