车间作业调度问题的仿真研究

Application of Job-Shop Scheduling Problem Based on Ant Colony Optimization Algorithm

研究车间作业调度优化问题,使资源、车辆调试、交通分配等达到优化配置,因此车间作业调度问题是一个多约束条件的目标优化问题,采用多项式求解方法不能获得最优解,导致车间作业调度效率低。为了提高车间作业调度效率,提出了一种蚁群算法的车间作业调度优化算法。首先以最小加工时间作为优化目标,蚂蚁爬行路径为作业调度方案,通过蚁群中个体间互相协作和信息交流获得最优车间作业调度方案。通过车间作业调度测试案例对算法进行验证性实验,实验结果表明,蚁群算法提高了车间作业调度效率,能在最短时间找到最优调度方案,为车间作业调度优化提供了依据。

Research job shop scheduling problem and make resources optimized configuration.The job-Shop scheduling problem is a NP-hard problem,and some polynomial solutions to the problem are not the best one,leading to low efficiency workshop scheduling problem.In order to improve the efficiency of job-Shop scheduling problem,a job-Shop scheduling method was put forward based on ant colony algorithm.Taking minimize processing time as optimal objective,ants crawling path as a job scheduling schemes,individuals collaboration and information exchanging in ant colony were carried out to obltain the optimal workshop scheduling solutions.The method was tested by job-shop scheduling problem,and the results show that the ant colony algorithm improves the efficiency,shortens the optimization time,and is effective for solving Job-Shop scheduling problem.