计算机工程与设计
計算機工程與設計
계산궤공정여설계
COMPUTER ENGINEERING AND DESIGN
2015年
6期
1530-1534
,共5页
PSO算法%协同优化%迭代%全局最优%收敛速度
PSO算法%協同優化%迭代%全跼最優%收斂速度
PSO산법%협동우화%질대%전국최우%수렴속도
PSO algorithm%collaborative optimization%iterative%globally optimal%convergence rate
传统PSO算法的收敛性能会随求解问题空间维数的增加而下降，根据协同进化原理，通过对传统PSO算法进行协同优化处理，设计一种改进的协同PSO算法。在每次迭代过程中，采用传统PSO算法更新粒子位置和速度，由此产生群体当前的全局最优位置；对所有粒子所经历的最优位置进行降维的协同优化，产生一个参考全局最优解；根据参考全局最优解更新群体当前的全局最优位置。仿真结果表明，该算法可以明显提高收敛速度，在某些问题上可以收敛到全局最优。
傳統PSO算法的收斂性能會隨求解問題空間維數的增加而下降，根據協同進化原理，通過對傳統PSO算法進行協同優化處理，設計一種改進的協同PSO算法。在每次迭代過程中，採用傳統PSO算法更新粒子位置和速度，由此產生群體噹前的全跼最優位置；對所有粒子所經歷的最優位置進行降維的協同優化，產生一箇參攷全跼最優解；根據參攷全跼最優解更新群體噹前的全跼最優位置。倣真結果錶明，該算法可以明顯提高收斂速度，在某些問題上可以收斂到全跼最優。
전통PSO산법적수렴성능회수구해문제공간유수적증가이하강，근거협동진화원리，통과대전통PSO산법진행협동우화처리，설계일충개진적협동PSO산법。재매차질대과정중，채용전통PSO산법경신입자위치화속도，유차산생군체당전적전국최우위치；대소유입자소경력적최우위치진행강유적협동우화，산생일개삼고전국최우해；근거삼고전국최우해경신군체당전적전국최우위치。방진결과표명，해산법가이명현제고수렴속도，재모사문제상가이수렴도전국최우。
Traditional PSO algorithms suffer from the curse of dimensionality which implies that their performances deteriorate as the dimensionality of the search space increases .A variation on the traditional PSO algorithms ,called improved cooperative par‐ticle swarm optimization or COPSO was proposed ,which employed cooperative behavior to significantly improve the performance of the original algorithms .Firstly ,traditional PSO algorithms were used to update the position and velocity vectors of particles , and then a reference global best position was obtained by using cooperative operator on the best positions of particles encountered so far . Such reference global best position was used to update the current global best position of the swarm .Application of the COPSO algorithm on the benchmark optimization problems shows a marked improvement on convergence rate of some traditional PSO algorithms .
