Integration of process planning and job shop scheduling using genetic algorithm

This study focused on the integration problem of process planning and scheduling in a job shop environment. In an effort to integrate process planning and scheduling by taking advantage of the flexibility that alternative process plans offer, we have designed a GA (Genetic Algorithm)-based scheduling method. The performance of this newly suggested GA-based method has been evaluated by comparing integrated scheduling with separated scheduling in a real company that has alternative process plans. Also, a couple of benchmark cases have been tested for performance evaluation, thus proving that the integrated scheduling shown by this research can be effectively applied to the real case.