Fast Convergence in Function Optimization Using Modified Velocity Updating in PSO Algorithm
In this paper, a new version of Particle Swarm Optimization (PSO) Algorithm has been proposed where the velocity update equation of PSO has been modified. A new term is added withthe original velocity update equation by calculating difference between the global best of swarm and local best of particles. The proposed method is applied on eight well known benchmark problems and experimental results are compared with the standard PSO (SPSO). From the experimental results, it has been observed that the newly proposed PSO algorithm outperforms the SPSO in terms of convergence, speed and quality.
Unable to display preview. Download preview PDF.
- 1.Eberhart, R.C., Kennedy, J.: A New Optimizer Using Particle Swarm Theory. In: International Symposium on Micromachine and Human Science, pp. 39–43 (1995)Google Scholar
- 2.Kennedy, J., Eberhart, R.C.: Particle Swarm optimization. In: IEEE International Joint Conference on Neural Networks, pp. 1942–1948. IEEE Press (1995)Google Scholar
- 3.Clerc, M.: Particle Swarm Optimization. ISTE Publishing Company (2006)Google Scholar
- 4.Englelbrecht, A.: Computational Intelligence: An Introduction. Halsted Press (2002)Google Scholar
- 5.Ziyu, T., Dingxue, Z.: A Modified particle Swarm Optimization with an Adaptive acceleration coefficients. In: Asia-Paciffic Conference on Information Processing (2009)Google Scholar
- 7.Zhan, Z.-H., Zhang, J., Li, Y., Chung, H.S.-H.: Adaptive particle swarm optimization. IEEE Transactions on Systems, Man, and Cybernetics, 1362–1381 (2009)Google Scholar
- 8.Xinchao, Z.: A perturbed particle swarm algorithm for numerical optimization. Applied Soft Computing, 119–124 (2010)Google Scholar
- 9.Chen, M.-R., Li, X., Zhang, X., Lu, Y.-Z.: A novel particle swarm optimizer hybridized with external optimization. Applied Soft Computing, 367–373 (2010)Google Scholar
- 10.Pedersen, M.E.H.: Tuning & Simplifying Heuristically Optimization, Ph.D. thesis, school of Engineering Science, University of Southampton, England (2010)Google Scholar
- 11.Singh, N., Singh, S.B.: One Half Global Best Position Particle Swarm Optimization Algorithm. International Journal of Scientific & Engineering Research 2(8), 1–10 (2012)Google Scholar
- 12.Shi, Y., Eberhart, R.C.: A modified particle swarm optimizer. In: Proceedings of the IEEE international Conference on Evolutionary Computation, pp. 69–73 (1998)Google Scholar
- 13.Shi, Y., Eberhart, R.C.: Parameter Selection in particle swarm Optimization. In: 7th Annual Conference on Evolutionary Programming, San Diego, USA (1998)Google Scholar