Abstract—This paper proposes a novel particle swarm optimization with passive congregation (PSOPC) algorithm based on the chaos phenomenon. The proposed Chaotic PSOPC (CPSOPC) algorithm utilizes chaotic sequences to improve the global searching by escaping the local optima. This algorithm overcomes the disadvantages of premature convergence in the PSOPC. We compared the proposed algorithm with PSOPC for eight benchmark functions with 10 and 20 dimensions. Simulation results indicate that the CPSOPC improves the global convergence of PSOPC. Furthermore, the proposed algorithm improves the accuracy and efficiency of searches compared with PSOPC and increases the convergence speed of PSOPC.

Index Terms—Chaotic sequences, particle swarm optimization, passive congregation, logistic map.

Reza Gholipour is with the Faculty of Electrical and Computer Engineering, Babol (Noushirvani) University of Technology, Babol, Iran (e-mail: reza_gh_08@yahoo.com).
HamedMojallali is with the Electrical Engineering Department, Faculty of Engineering, University of Guilan, Rasht, Iran (e-mail: mojallali@guilan.ac.ir).
Seyed Mohammad KazemAkhlaghi is with the Faculty of Mechanical Engineering, Babol (Noushirvani) University of Technology, Babol, Iran (e-mail: smk_akhlaghi@yahoo.com).

Cite: Reza Gholipour, Hamed Mojallali, and Seyed Mohammad Kazem Akhlaghi, "A Novel Particle Swarm Optimization with Passive Congregation via Chaotic Sequences," International Journal of Computer and Electrical Engineering vol. 4, no. 6, pp. 809-815, 2012.