基于粒子群搜索策略的混合果蝇优化算法

Hybrid Fruit Flies Optimization Algorithm Based on Particle Search Strategy

果蝇优化算法是一种群智能优化算法,它存在一些缺点如在后期收敛速度和求解精度等方面。论文提出一种基于粒子群搜索策略的混合果蝇优化算法,充分利用PSO算法中个体极值和全局极值位置来更新果蝇个体位置,从而弥补了果蝇优化算法的不足。为了验证该算法的性能通过测试6个标准多元非线性函数并且与标准果蝇优化算法相比较,测试结果表明该算法的收敛性和求解精度都得到了提高。

Fruit flies optimization algorithm is an intelligent optimization algorithm,which has some shortcomings in such aspects as convergence speed and precision,etc in the later period.This paper presents a mixed fruit flies optimization algorithm based on particle swarm search strategy,making full use of individual extremum and global extremum position in PSO algorithm to update the individual position of fruit flies,so as to make up for the deficiency of the fruit flies optimization algorithm.In order to verify the performance of the algorithm,six standard multivariate nonlinear functions are tested and this algorithm is compared with the standard fruit flies optimization algorithm.With the test results shows that the proposed algorithm’s convergence and accuracy are both improved.