【摘要】 提出了带组织的粒子群优化算法。粒子群优化算法是一种基于群体智能的演化算法,具有良好的优化性能。但由于群体的迅速收敛和多样性低,导致算法早熟收敛。依据人类社会活动的特点,在粒子群中引入组织的概念,定义了组织的优胜劣汰。在组织优胜劣汰的过程中,更新最差组织,进而保持粒子群的多样性,避免算法的早熟收敛问题。仿真实验表明:OPSO比PSO有更好的优化能力。更多还原

【Abstract】 Particle swarm optimization algorithm with organization(OPSO) is presented.Particle Swarm Optimization(PSO) Algorithm with Organization is an evolutionary algorithm based on population intelligence and exhibits good performance on optimization.However,it will fall into premature convergence due to the fast convergence of population and the decrease of population diversity.Based on the characteristics of human society,organization is added to the OPS algorithm,and survival of the fitter is defined.In the course of survival of the fitter,the worst organization is renovated in order to keep the variety of particle swarm and escape from premature convergence.Experiments show that OPSO outperforms standard PSO.更多还原