利用改进的郭涛算法求解函数优化问题

对郭涛算法做了两点改进:一是引入演化策略中的高斯变异算子,二是引入自适应搜索子空间。高斯变异算子对群体作正态分布微调,防止早熟;自适应搜索子空间使得群体在演化至接近全局最优解时能自动缩小搜索范围,从而达到加速收敛的目的。数值试验表明:新算法正确高效,求解精度高;指出并更正了文献中的两处错误,所用测试函数全局最小值均刷新了文献中记载的最好结果。

An Improved Guo's Algorithm for Solving Function Optimization Problem

Based on the GUO's Algorithm, a high-efficiently hybrid evolutionary a lgorithm is proposed. The new algorithm has two main characteristics: first, int roduce the Gauss mutation operator of Evolution Strategies (ES) ; second, introd uce variable searching subspace. In order to avoid premature of population , the Gauss mutation operator is used ; at the same time , for accelerating convergen ce, the searching subspace can be reduced automatically when the population's ev olutionary value is very close to the global best value of the population. Numer ical experiments show that the new algorithm is high-efficiency and the precisio n of results is very high, at the same time, the experiments' results of several test functions exceed the best value recoded in the references.