An Improved Particle Swarm Optimization Algorithm based on Membrane Structure

Presented a new hybrid particle swarm algorithm based on P systems, through analyzing the working principle and improved strategy of the elementary particle swarm algorithm. Used the particles algorithm combined with the membrane to form a community, particles use wheel-type structure to communicate the current best particle within the community. The best particles, as Representative, compete for the optimal particle of the higher level. Utilized the Objective Functions to test the designed algorithm performance, compared with other particle swarm optimization algorithms, the experiment results shown that the designed algorithm has better performance in seeking Optimization solution quality, robustness and convergence speed.