粒子群算法在车间作业调度问题中的仿真研究

摘要

研究车间作业调度问题,优化资源配置.车间作业度问题(JSP)是一类典型的NP-hard问题,针对传统方法在JSP应用过程中,存在速度慢、易陷入局部最优,导致车间作业调度效率低.为了解决车间作业调度效率低的难题,提出了一种粒子群算法的车间作业调度方法.该方法将每个粒子代表一种作业调度方案,以最小化加工时间作为算法的优化目标,通过粒子群之间的协作来获得最优作业调度方案.采用JSP标准测试案例在Matlab平台上对该方法进行了验证性实验,实验结果表明,相对于传统方法,该方法能够在最短时间找作业调度的最优解,提高了车间作业调度效率,是一个求解车间作业调度问题的有效方法.%Job shop scheduling problem (JSP) is studied to optimize the allocation of resources. JSP is a typical NP-hard problems, the traditional method is slow and easily falling into local optimum and the scheduling efficiency is extremely low. In order to improve the scheduling efficiency, this paper put forward a job shop scheduling method by PSO. The method takes each particle as a scheduling program, and minimizing the processing time as the optimization goal, the optimal scheduling scheme is got through particle swarm. The test is carried out by the JSP standard test on Matlab, the experimental results show that, compared with traditional methods, this method can find the optimal solution in the shortest time to find the optimal solution, has improved job-shop scheduling efficiency.