Title :
Convergence analysis of the particle swarm optimization with stochastic inertia weight
Author :
Qingguo, Wang ; Wenjun, Yan ; Wei, Yao
Author_Institution :
Coll. of Electr. Eng., Zhejiang Univ., Hangzhou, China
Abstract :
This paper summarized the convergence research of PSO and analyzed the global convergence of the swarm optimization particle algorithm(PSO) with stochastic inertia weight. At present,dealing with optimization problems in Engineering applications, PSO with stochastic inertia weight was always used, and had good performance. However, its theoretical foundation about stability was still relatively weak. Based on the theory of stochastic processes and the previous theoretical achievements, this paper presented a convergence condition for the stochastic weight system. Compared with the methods in the previous literature, the proposed method achieves better results. Simulations demonstrate the validity of the proposed method.
Keywords :
convergence; particle swarm optimisation; stochastic processes; PSO; convergence analysis; particle swarm optimization; stochastic inertia weight; Convergence; Electrical engineering; Optimization; Particle swarm optimization; Stability analysis; Stochastic processes; convergence; particle swarm optimization(PSO); stochastic inertia weight;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5555059