Inventory sorting rules and dispatching strategies for scheduling jobs in FMSs using a real-time genetic algorithm

The basic concepts of scheduling process are commonly based on the allocation of limited resources to tasks and jobs at certain specified times. Scheduling techniques aim commonly to minimize, makespan, number of tardy jobs, cost, and/or maximizing revenue. In the current paper a dynamic scheduling system is introduced. The system is capable of generating optimized schedules of jobs in FMS environments using genetic algorithms. The proposed approach seeks the best processing sequence at loading station and takes into account the buffer capacity and the time of transport operation constraints for minimizing the makespan objective. The performance of the solution approach is compared with the results of using traditional dispatching rules. A comparison with other works shows that the proposed genetic algorithm leads to promising results.