Cloning Particle Swarm Optimization with Hybrid Discrete Variables and its Application to Gear Reducer

摘要：

During the iterative process of standard particle swarm optimization (PSO), the premature convergence of particles decreases the algorithms searching ability. Through analyzing the reason of particle premature convergence during the renewal process, introducing the updating strategy based on cloning technique, cloning particle swarm optimization (CPSO) algorithm with hybrid discrete variables model was proposed, and its program CPSO1.0 with Matlab soRware was developed. The updating strategy based on doning algorithm makes the particles of cloning particle swarm optimization (CPSO) maintain the dwersity during the iterative process, thus overcomes the defect of premature convergence. Example of gear reducer indicates that compared with the exiting algorithms, CPSO gets the best result, thus certify the improvement of the algorithms searching ability by cloning mechanism.

关键词： Cloning particle swarm optimization Cloning Algorithm gear reducer hybrid discrete variables

作者: Youxin LUO Bin ZENG

作者单位: College of Mechanical Engineering Hunan University of Arts and Science Changde,415000,P.R.China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 395-398

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）