Dynamic schedule optimization based on correlation scheduling model

To reflect scheduling constraints and priority rules, a scheduling model is described with the scheduling nodes. A correlation model is established for the job shop scheduling. Constraint relationship is described with the scheduling nodes and the solution chains. Uncertain factors are taken account into the actual scheduling process that the schedule model is imported to the fuzzy job-shop problems. The correlation method was utilized to obtain the feasible schedule solutions. The primary solutions are optimized with the ACO algorithm to obtain the finally scheduling solution. Simulation results show that the method can obtain a optimal scheduling scheme when the processing time and delivery are uncertain.