Aiming at particles with different fitness value needing for different search capabilities, this paper presents an adaptive particle swarm optimization algorithm with dynamically adjusting parameters. The concept of particle relative excellent degree is introduced to dynamically adjust inertia weight and accelera- tion coefficient, which improves the performance of the globe search and local search and maintains particle individuality. Experiment simulations of three benchmark functions show that the proposed al...
