We proved the convergence of GA which we proposed adaptive fitness functions, adaptive crossover probability and adaptive mutation probability.
最后，对提出的自适应交叉概率和自适应变异概率利用遗传算法的公理化理论进行了收敛性的证明。
Genetic algorithms mimic Darwinian natural selection, where "fitness" selects individuals for survival, breeding, and, hence, adaptive mutation.
遗传算法模仿达尔文的自然选择，其中“适应性”选择进行生存、繁殖以及由此而来的适应性变异的个体。
According to the changes of the fitness, updated the inertia weight of each particle after each iteration to achieved a self-adaptive adjustment of global search ability and local search capabilities.
在每次迭代时，算法可根据粒子的适应度变化动态改变惯性权重，从而使算法具有动态自适应性全局搜索与局部搜索能力。
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