中文摘要：

并行优化算法是一种以优化算法为基础,利用并行计算技术,把问题分解到各个处理器进行处理的算法。以遗传算法为蓝本,提出一种降维式自主迁移的伪并行遗传算法。该算法实现了对高维问题的并行降维优化,并设计出新颖的具有协作性质的信息迁移机制,更好地融合各个处理器的优化信息。测试了3种不同的迁移处理器中优化信息的方法,并对11个具有30维的连续函数进行测试。测试结果与其它并行遗传算法进行了比较,该方法在求解精度和速度上都要比传统的串行遗传算法和并行遗传算法优胜。

英文摘要：

Parallel genetic algorithm is a kind of random optimization algorithm, which utilizes parallel technique to assign workload to different processors. A pseudo-parallel genetic algorithm with cooperative dimensional reduction and self-migration is proposed. The dimensions of the problem is successfully reduced and a strategy on selecting contents of migration is proposed. Numerical experiments on high dimensional functions are tested, and the results show that the proposed algorithm can achieve better performance than the traditional serial genetic algorithm and other parallel genetic algorithms on success rate, accuracy and speed.