Journal of Northeastern University(Natural Science)

Journal of Northeastern University ›› 2011, Vol. 32 ›› Issue (12): 1692-1695.DOI: -

• OriginalPaper • Previous Articles     Next Articles

An improved particle swarm optimization algorithm

Wu, Pei-Feng (1); Gao, Li-Qun (1); Zou, De-Xuan (2); Yi, Yu-Feng (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110819, China; (2) School of Electrical Engineering and Automation, Xuzhou Normal University, Xuzhou 221116, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-04-04
  • Contact: Wu, P.-F.
  • About author:-
  • Supported by:
    -

RichHTML

1

PDF (PC)

2336

Abstract: An improved particle swarm optimization (EDAPSO) algorithm is proposed. The improved algorithm integrates the exploration of estimation of distribution algorithm (EDA) and the exploitation of the particle swarm optimization (PSO) algorithms. The EDAPSO algorithm is applied to solve unconstrained optimization problems and the results of the EDAPSO algorithm are compared with the results of other three classical PSO algorithms. The experimental results for unconstrained optimization problems show that the EDAPSO may find better solutions and has higher numerical stability. The EDAPSO algorithm is then applied to solve the economic dispatch problems of power system with 13 units. Experimental results show that the solution obtained by the EDAPSO algorithm is better than that reported in recent literatures.

CLC Number: