一种基于权重优化的σ策略的微粒群优化算法

摘要

微粒群算法是一种受鸟类和鱼类群体行为启发而产生的一种智能化计算方法，针对微粒群算法易于陷入局部最优的缺点，对标准PSO算法进行了改进，提出了一种更为简化的PSO算法，即σ-PSO。在σ-PSO中，用相位角的增量代替速度的增量，通过绘制相位角来确定微粒的位置。用这种新的权重优化算法与标准PSO算法对大学生的评价进行仿真的结果进行比较，证明该算法具有一定的优越性。%Particle swarm optimization algorithm is developed under the inspiration of behavior laws of bird flocks, fish schools and human communities. Aiming at the disadvantages of particle swarm optimization algorithm which is trapped easily into a local optimum, this paper improves the standard PSO and proposes a new algorithm. In this paper, a more simple strategy of PSO algorithm called σ- PSO is proposed. In σ-PSO, an increment of phase angle vector replaces the increment of velocity vector and the positions are decided by the mapping of phase angles. It uses the new algorithm to compare the weight optimization algorithm with the standard PSO algorithm for the college student evaluation, and the results show that the new algorithm is efficient.