一种混合的GOA-GA优化算法

A Hybrid GOA-GA Optimization Algorithm

本文融合了网格算法(GOA)和遗传算法(GA),形成了一种混合GOA-GA算法进行函数优化问题的求解。网格算法作为一种定向的全局搜索算法,避免了大量的盲目搜索过程,同时不易陷入局部最优。遗传算法作为局部搜索能力较强的智能优化算法,在一些全局较好群体的基础上,采用随机优化技术能够较快地收敛到全局最优解。通过数值试验特别是对高维优化问题,算法体现出收敛速度快、精确性高、不宜陷入局部最优等优点。

The paper combined Gridding Optimization Algorithm（GOA） and Genetic Algorithm（GA）,a hybrid GOA-GA algorithm is proposed for function optimization,As a global determinate search algorithm,GOA can avoid Large number of blind searching,as well as avoid getting into local minima.GA can quickly get into a global minimum with random optimization technology based on a number of better minima as its strong local search ability.GOA-GA has some advantages as fast convergence 、high-precision and global optimization through experiment comparing to GOA and GA.