【摘要】 针对一类函数优化问题,通过对粒子群优化算法的惯性权重和算法公式的分析,提出了一种改进的粒子群优化算法。该算法突破惯性权重常规取值。实验证明:该算法可以提高算法的效率,用极少次数的迭代,使原本复杂甚至不能求解的问题得以解决。算法具有迭代次数少、对高维函数的鲁棒性强与空间复杂度低等优势。更多还原

【Abstract】 An improved PSO algorithm,for a family of function optimization problems whose solutions are distributed in the vicinity of origin,is proposed via analyzing of the inertia weight and particle swarm optimization formula.The experimental results demonstrate that,the algorithm can greatly improve the efficiency of algorithms,with very few number of iteration,so that the original complex problem solving should not even be resolved.Moreover,the improved algorithm is characterized by fewer iteration,less sensitivity to the dimensions of target functions as well as lower space complexity.更多还原