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The parallel test has become the developmental trend of Automatic Test System with great strength in reducing test time and test cost. Aimed at the problems that task scheduling is complex and task optimization is difficulty in parallel automatic test, a improved Discrete Particle Swarm Optimization (DPSO) algorithm is proposed, in which problem space coding is redefined and particle position update formula is rebuilt using crossover and mutation operator. And then the objective function and constraint condition of task scheduling for parallel test are given, according to the limit completion time theorem of parallel test. In order to validate the performance of the improved DPSO algorithm, a parallel test simulation experiment for three pieces of circuit board is made by parallel test system of certain radar electronic equipment, and the optimal task scheduling is got. The results show that compared with genetic algorithm the improved DPSO algorithm has less iterations, higher efficiency and better optimal performance, and is more suitable for engineering application.