Two new parallel algorithms based on QPSO
Based on the analysis of classical particle swarm optimization (PSO) algorithm,we adopted Sun’s theory that has the behavior of quantum particle swarm optimization (QPSO) algorithm,by analyzing the algorithm natural parallelism and combined with parallel computer high-speed parallelism,we put forward a new parallel with the behavior of quantum particle swarm optimization (PQPSO) algorithm.On this basis,introduced the island model,relative to the fine-grained has two quantum behavior of particle swarm,m optimization algorithm,the proposed two kinds of coarse-grained parallel based on multiple populations has the behavior of quantum particle swarm optimization (QPSO) algorithm.Finally under the environment of MPI parallel machine using benchmark functions to do the numerical test,and a comparative analysis with other optimization algorithms.Results show that based on the global optimal value is superior to the exchange of data based on local optimum values of exchange,but in the comparison of time is just the opposite.
Particle swarm Parallel Island model Qquantum
Yuxia Qian Ke Dong Xiaonuo Zhang
The department of informationn engineering, Shandong water polytechnic,Rizhao, China The department of mechanical engineering ,Shandong water polytechnic,Rizhao, China School of information science and engineering ,Rizhao polytechnic,Rizhao, China
国际会议
重庆
英文
325-332
2015-03-21（万方平台首次上网日期，不代表论文的发表时间）