Parallel test using natural coding genetic algorithm

Considering parallel test task scheduling in automatic test system is complicated and difficult to optimize, a task scheduling arithmetic based on natural coding genetic algorithm is proposed. This arithmetic transforms searching parallel test tasks sequences into searching serial test tasks sequences. The natural coding genetic algorithm, which could improve efficiency, is applied to search for optimum or near optimum sequences. The serial test tasks sequences are regarded as chromosomes, which are selected, crossed, and mutated. According to the simulating results, using this method the optimum or approximate optimum result could be gain quickly. The effect of the operators is analyzed, and then the schema theorem is presented, which proves the rationality of genetic algorithm used.