基于蚁群算法的并行测试任务调度

并行测试的任务优化调度是并行测试技术的核心问题.提出了一种用于解决并行测试任务调度问题的改进蚁群算法,通过该算法可以获得测试时间最短的任务调度序列.给出了并行测试任务调度问题的数学模型,设计了启发式函数和状态转移概率的计算公式.采用动态标注方法在搜索过程中加大可行解间的信息素差别,避免算法早熟.给出了应用实例,实际应用表明该算法是有效的,能很好地解决此类多维动态组合优化问题.

Novel Ant Colony Algorithm for Parallel Test Task Scheduling

The optimized parallel test task scheduling is a key problem to the parallel test. A novel ant colony algorithm was proposed to optimizing the parallel test task scheduling. With this algorithm, the task sequence with shortest total test time could be obtained. The mathematical model of the problem of parallel test task scheduling was established. The calculate formulae of heuristic information and probability of selecting were given. An approach of dynamic labeling to increase the pheromone difference between feasible solutions was adopted to avoid earliness of algorithm. Two examples were given. The practice application shows that this method is validated and can solve complex multidimensional dynamic combinatorial optimization problems.