Research and Application Job-shop Scheduling in MES Based on Hybrid of GA/SA

Abstract

In manufacturing execution system (MES), Since scheduling of multiple projects is a complex and time-consuming task, a large number of heuristic rules have been proposed by researchers for such problems. However, each of these rules is usually appropriate for only one specific type of problem. Since the Genetic Algorithm (GA) has its immanent limitations and the Simulated Annealing (SA) Algorithm has the advantages in some aspects, combined these two algorithms together just achieve the perfection. In view of this, a hybrid of GA and SA (GA-SA Hybrid) is proposed in this paper to solve job-shop scheduling problem. The algorithm making the crossover and mutation probability adjusted adaptively and nonlinearly with the completion time, can avoid such disadvantages as premature convergence. The approach is tested on a set of standard instances and compared with other approaches. The Simulation results validate the effectiveness of the proposed algorithm.