基于有色Petri网和IPSO的并行测试系统任务调度研究

Research on Task Scheduling for Parallel Test System Based onColored Petri Net and IPSO Algorithm

并行测试以减少测试时间和降低测试成本的强大优势成为下一代自动测试系统ATS发展的热点;针对ATS中并行测试任务调度复杂、难以优化问题,提出了一种有色Petri网和改进粒子群优化(IPSO)算法相结合的任务调度优化算法;采用有色Petri网建立并行测试系统模型,得到并行测试的动态特性;采用IPSO算法搜索最优的任务调度路径,得到以测试时间最短为目标的最优任务调度方案;最后,将该算法应用到某型雷达电路板并行测试系统中,研究结果表明,与遗传算法GA相比,该算法效率更高,更利于工程应用。

The Parallel test has become the hot issue of next generation Automatic Test System with great strength in reducing test time and test cost. According to the problems of complex task scheduling and difficult optimization in automatic test system, we propose a task scheduling optimization algorithm based on colored Petri nets and improve PSO （IPSO） algorithm. The dynamic characteristic of parallel test is got from parallel test system model established by colored Petri nets. The optimal scheduling scheme is got with shortest time using IPSO algorithm by searching for the optimal task scheduling path. Furthermore, the proposed algorithm is applied in certain parallel test system for radar. Compared with the genetic algorithm, the results of the study show that it is more efficient and is in more favor of project applications.