一种基于极坐标编码的果蝇优化算法

针对果蝇优化算法易陷入早熟收敛、收敛速度慢、寻优精度低的缺点,提出一种基于极坐标编码的果蝇优化算法.为提高果蝇优化算法的寻优精度,采用极坐标编码的形式,以增加单个母体寻优空间表示方法的多样性,并使种群中的个体,在围绕个体的整个超球体内随机搜索,使个体的搜索范围更加广泛.在迭代寻优过程中,根据适应度值和概率调整极角,逐渐降低观测结果的不确定性.通过9个基准测试函数,对基于极坐标编码的果蝇优化算法进行仿真实验,结果表明了算法在收敛性和稳定性方面,优于其它5个优化算法,测试结果验证了极坐标编码方法的有效性和可行性.

An Fruit Fly Optimization Algorithm Based on Polar Coordinate Coding

In order to overcome the demerits of easily getting into local extremum,slow rate of convergence and low convergence precision in fruit fly optimization algorithm,an improved FOA called polar coordinate coding of fruit fly optimization algorithm(PCFOA) is proposed.In order to improve the accuracy in searching,polar coordinate coding is employed to increase diversity in the expression solution of single matrix solution space,which makes the individual in the population search randomly surrounding the super sphere,the individual search range wider The polar angle is adjusted under probability by fitness though the iterative process,so that the uncertainty of observations is reduced gradually.Nine benchmark test functions are tested and five other optimization algorithm contrast experiments are carried out results.It shows that the PCFOA is superior to the other five optimization algorithms on the convergence and stability,and finally the effectiveness of the algorithm is verified by the standard test functions.