A Hybrid Particle Swarm Algorithm Based on Adaptive Local Search

摘要

In this paper, a hybrid particle swarm optimization algorithm based on adaptive local search (PSOALS) is proposed. During the global searching process, the adaptive local search operator which can adjust the neighborhood space adaptively in response to the current state of the population is used to enforce the local exploitation ability of the particles. Comparing experiments are made, and the results show that PSOALS is effective and efficient in enhancing the accuracy and convergence.