基于岛屿群体模型的并行粒子群优化算法

为改善粒子群优化算法对大规模多变量求解的性能，提出了基于岛屿群体模型的并行粒子群优化算法．对粒子群优化算法机理和本质并行性进行分析，设计和实现了一种并行粒子群优化算法．实验结果表明，基于岛屿群体模型的并行粒子群优化算法不仅提高了求解效率，而且改善了早收敛现象，算法的性能比经典粒子群优化算法有了很大提高．

Parallel Particle Swarm Optimization Algorithm with Island Population Model

A novel algorithm of parallel particle swarm optimization with island population model is proposed to improve the performance of particle swarm optimization algorithm for application to large-scale problems and multivariable solutions. The parallel particle swarm optimization algorithm is designed and implemented using an idea of island population model. The experimental results show that not only the solving efficiency is raised but also the restraining premature convergence is enhanced in the parallel algorithm. Comparing with classical particle swarm optimization, the performance of the proposed algorithm is greatly improved consequently.