%0 Journal Article
%A GU Qinghua
%A MENG Qianqian
%T Hybrid Particle Swarm Optimization and Pigeon-Inspired Optimization Algorithm for Solving Complex Functions
%D 2019
%R 10.3778/j.issn.1002-8331.1808-0151
%J Computer Engineering and Applications
%P 46-52
%V 55
%N 22
%X In order to solve the complex function optimization problems, a two-stage hybrid optimization algorithm is proposed. The basic particle swarm optimization and pigeon-inspired optimization algorithm are improved. The inertia factor and jump operator are used to enhance the searching ability of particle swarm optimization, and the interference operator is used to increase the population diversity of pigeon-inspired optimization. The improved algorithm is combined to form the two-stage hybrid optimization algorithm. Meanwhile, a diversity function is defined to detect the population diversity in real-time monitoring to ensure the diversity of the population. The simulation results show that the algorithm is suitable for solving complex function optimization problems, and has good convergence speed and convergence accuracy.
%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1808-0151