New Particle Swarm Optimization Algorithm Incorporating Reproduction Operator for Solving Global Optimization Problems

This paper presents a new variant of Basic Particle Swarm Optimization (BPSO) algorithm named QI-PSO for solving global optimization problems. The QI-PSO algorithm makes use of a multiparent, quadratic crossover/reproduction operator defined by us in the BPSO algorithm. The proposed algorithm is compared it with BPSO and the numerical results show that QI PSO outperforms the BPSO algorithm in all the sixteen cases taken in this study.

[1]  Andries Petrus Engelbrecht,et al.  Fundamentals of Computational Swarm Intelligence , 2005 .

[2]  Vladimiro Miranda,et al.  EPSO-evolutionary particle swarm optimization, a new algorithm with applications in power systems , 2002, IEEE/PES Transmission and Distribution Conference and Exhibition.

[3]  Xin Yao,et al.  Fast Evolutionary Programming , 1996, Evolutionary Programming.

[4]  Vladimiro Miranda,et al.  EPSO - best-of-two-worlds meta-heuristic applied to power system problems , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[5]  Peter J. Angeline,et al.  Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences , 1998, Evolutionary Programming.

[6]  James Kennedy,et al.  The particle swarm: social adaptation of knowledge , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[7]  M. Montaz Ali,et al.  Population set-based global optimization algorithms: some modifications and numerical studies , 2004, Comput. Oper. Res..

[8]  Dou Quan Swarm-Core Evolutionary Particle Swarm Optimization , 2005 .

[9]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[10]  P. J. Angeline,et al.  Using selection to improve particle swarm optimization , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[11]  Yuhui Shi,et al.  Particle swarm optimization: developments, applications and resources , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[12]  Russell C. Eberhart,et al.  Swarm intelligence for permutation optimization: a case study of n-queens problem , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[13]  Xin Yao,et al.  Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..

[14]  Chu Kiong Loo,et al.  A new class of operators to accelerate particle swarm optimization , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..