关键词: 高维函数优化, 粒子群算法, 人工鱼群算法, 混合优化算法

Abstract: When the Particle Swarm Optimization（PSO） algorithm is easy to concentrate near the optimal particle, the particle motion ability is lost and the population is stagnant, so the optimization effect is not ideal. In this case, a new hybrid optimization algorithm is developed to solve these problems by combining the aggregation and foraging behavior of the Artificial Fish Swarm Algorithm（AFSA） with the particle swarm optimization algorithm. Finally, simulation experiments show that the hybrid optimization algorithm has excellent performance in the optimization of high-dimensional functions.

Key words: optimization of high dimensional function, particle swarm optimization, artificial fish swarm algorithm, hybrid optimization algorithm