遗传算法的研究和改进

The research of improved genetic algorithm

从原理及应用2个方面对遗传算法、蚁群算法、混洗蛙跳算法做了对比分析.针对遗传算法的不足之处,提出了相应的改进方法,并对改进后的遗传算法和经典的遗传算法做了应用比较.结果表明,改进后的遗传算法不仅提高了其收敛概率和收敛速度,而且具有更强的全局搜索能力,适用于求解复杂多峰值函数优化问题.

From two aspects of principle and application, GA, ACA and SFLA are contrasted. Aiming at the deficiency of GA, the corresponding improvement method is proposed, applications of improved and classical GA are compared. The results show that improved GA not only improves convergent speed, but also convergent probability and global searching ability, it is suitable for solving complex multimodal function optimization problems.