Research On Job-Shop Rescheduling Method Based On Real-Time Operating Information

Scheduling problem is a kind of important and difficult combinatorial optimization problem, the solution is quite difficult. Effective production scheduling methods can greatly improve production efficiency and the utilization of production resources. The core issue of production scheduling is model and algorithm, the effective scheduling algorithm is an important research content of production scheduling problem. Scheduling problem has high complexity and uncertainty, often suffer the disruption of Real-Time operating Information change, such as machine breakdown, suddenly interjecting of the workpiece, suddenly cancelling of the workpiece, advancing of the due data time. This paper, mainly aims at unprocessed artifacts for rescheduling after the system interruption. Through the survey of a factory production processes, this paper aims at single machine, flowshop, jobshop of the factory production scheduling for scheduling and rescheduling. First of all, through the survey, the paper analyzes the process of a factory production order, aims at the change case of three kinds of Real-Time operating information for rescheduling, using corresponding strategies and methods. Then the paper introduces the genetic algorithm that can solve the NP-hard, lays a theoretical foundation for solving the NP-hard problems such as flowshop, jobshop. Aiming at flowshop, separately adopting CDS heuristic algorithm, genetic algorithm, the paper carries through static scheduling to the system, by comparing genetic algorithm is indeed the optimal scheduling. And then it uses genetic algorithm to reschedule the interrupted system, experiments show that the optimized system get good results. For jobshop, the paper adopts genetic algorithm and indirect encoding based on machine attribute to solve the objective function, good results are obtained. Through experimental comparison, This method is superior to methods in the55literature. When the jobshop system occurs dynamic disruption, we still use the arithmetic of this paper to reschedule the system, by experimental test, the optimized sorting cost is significantly less than the original sorting cost. Therefore numerical example shows that the algorithm of this paper is not only feasible, but also has the advantages of concise and efficient.