遗传算法的研究与改进

The detailed ideas about improved Genetic Algorithm

遗传算法是基于自然界进化遗传的本质而形成的,包括选择、交叉、变异等过程,是求解最优解问题的优质算法。但是由于传统的遗传算法本身也存在着一定不稳定性,因此本文对于求解最优和最稳定数值的遗传算法意义做一定概述和算法思想描述,同时对于如何优化也有一定详述。例如:避免过早收敛、保证算法多样性以及提升算法的运算速度等。

Genetic algorithm is based on the nature of the evolutionary genetic in nature and form, including selection, crossover and mutation process, is a good algorithm for solving the optimal solution problem. But there exists a certain instability due to the genetic algorithm itself, so this paper for solving the optimal and most stable numerical significance of genetic algorithm to do a certain overview and description algorithm thought, also have some details on how to optimize. For example： diversity and avoid premature convergence and ensure algorithm improve computing speed of the algorithm, etc.