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。 Task scheduling in parallel testing is a core issue of parallel testing techniques. An improved ant colony algorithm is proposed to solve the parallel test task scheduling problem. By this algorithm, the task scheduling sequence with the shortest test time can be obtained. The mathematical model of parallel test task scheduling problem is given, and the formulas of heuristic function and state transition probability are designed. The dynamic annotation method is used to increase the pheromone difference between feasible solutions in the search process and avoid the algorithm premature. The application examples are given. The practical application shows that the algorithm is effective and can solve such multidimensional dynamic combinatorial optimization problems well.