Development And Simulation Analysis Of Job-shop Scheduling System

Job-shop production, a pattern extensively exists in actual production, as the fierce market competition and the customer's individual requirement, is going in the direction to rich variety, small lots, the delivery time ensured and inventory reduced. To satisfy the development of modern economic society and production technology as well as the customer's demands, the primary focus has been on the flexible job-shop production with routing flexibility which closely reflects the link between theoretical research and requirements of actual production.Rule-based scheduling, an intuitive, simple and practical method characterized by dynamics and low computational complexity, is preferred in real-world production scheduling. However, as a local decision maker with global sensitivity and lack of controls to optimization, rule-based scheduling can not generate satisfied schedule scheme. An iterative optimization method with state performance feedback control strategy is introduced to overcome the shortcoming of traditional rule dispatching.A feedback control strategy defined is applied to the software development for job-shop scheduling using rule-based iterative optimization. According to routing flexibility whether or not to be considered, the effects of scheduling objective functions as well as dispatching rules are analyzed independently by scheduling simulation, which are helpful to schedule effectively.As the performance criteria of device average utilization and job average tardiness, simulation is experimented on 198 benchmark instances divided into three groups to evaluate performance under eighteen dispatching rules. The simulation results demonstrate that the iterative optimization scheduling can improve performances effectively, the higher routing flexibility, the higher performance improved.