Solution of dynamic flexible job shop scheduling under maintenance constraints

Scheduling problems encountered in flexible job shop systems are combinatorial optimization problems which are non-deterministic polynomial time class and different from the classical job shop scheduling problems, besides sequencing of operations, assigning of jobs to parallel machines are also taken into consideration in the problems. These problems are turned into o dynamic flexible job shop scheduling problems due to the fact that parallel machines are not always available and due to the dynamics events encountered in real life and the solution becomes difficult. Many methods have been developed in order to achieve faster and more effective results for solving these problems. In this study, robust scheduling problem are addressed for dynamic flexible job shop production systems where new jobs arrivals and machines are sent for maintenance in certain periods. In the solution of the problem, mathematical models of different re-scheduling methods (Robust, Non-delay Schedule and End-Inserted Schedule) were compared. The proposed models were evaluated using different performance variables (machine occupancy rate, delays and maximum completion time) over a total of 45 problem scenarios for different maintenance periods and new job arrival times with experimental data sets. According to the results obtained, the average machine occupancy rate in the Robust schedule was 72% in these scenarios and it gave better results than the other methods.