应用遗传算法原理确定函数的最优解_乔均俭

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  本文主要介绍了一种新型的、随机性的全局优化方法即遗传算法。一般应用于在一个问题的解集中查找最优解情况, 如是一个问题有多个答案,但是想查找一个最优答案的话,那么使用遗传算法可以达到更快更好的效果。即在浮点编码遗传算法中加入一个函数,构成适于不可微函数全局优化的遗传算法。该算法改善了遗传算法的局部搜索能力,显著提高了遗传算法求得全局解的概率(This paper introduces a new stochastic global optimization method, genetic algorithm. Generally, it is applied to find the optimal solution in the solution set of a problem. If there are multiple answers to a problem, but want to find an optimal answer, then the genetic algorithm can achieve faster and better results. That is to say, a function is added into the floating point coding genetic algorithm to form a genetic algorithm suitable for global optimization of non-differentiable functions. This algorithm improves the local search ability of genetic algorithm and significantly improves the probability of global solution)