基于改进伪并行遗传算法的函数优化

Function Optimization Based on the Improved Pseudo-Parallel Genetic Algorithm

针对遗传算法早熟和收敛速度慢的问题,在已有的伪并行遗传算法基础上对遗传操作进行改进。采用3个测试函数对改进的算法进行验证,结果表明改进的算法在函数的平均适应度值、平均运行代数、收敛概率等方面都取得了较好的结果。

For the problem of prematureness and slow convergence of Genetic Algorithm, some improvement based on apseudo-parallel genetic algorithm are made in aspects of genetic manipulation. Three test functions are used to verify the improved algorithm. The results show that the average fitness value, the average run algebra, and probability of convergence have achieved better results.