Journal of Software, Vol 6, No 4 (2011), 604-611, Apr 2011
doi:10.4304/jsw.6.4.604-611

A Novel PSO Algorithm Based on Local Chaos & Simplex Search Strategy and its Application

Shengli Song, Yong Gan, Li Kong, Jingjing Cheng

Abstract


To improve particle swarm  optimization (PSO) computing performance, the centroid of particle swarm is firstly introduced in standard PSO model to enhance inter-particle cooperation  and information sharing capabilities, then combining randomness and ergodicity of the strong chaotic motion and fast convergence of the simplex method, a novel particle swarm optimization algorithm with adaptive space mutation (CSM-CPSO)  is proposed to improve local optimum efficiency and global convergence performance of PSO algorithm. Results of Benchmark function simulation and  the material balance computation (MBC) in alumina production show the new algorithm has not only steady convergence and better stability,  but also higher precision and faster convergence speed, and also can avoid the premature convergence problem effectively.


Keywords


Particle Swarm Optimization;Centroid;Chaos; Simplex;Information Sharing

References


[1] J. Kennedy, R. C. Eberhart,”Particle swarm optimization,” Proceedings of the IEEE International Conference on Neural Networks IV, IEEE Press, Piscataway, NJ (1995), pp.1942–1948.

[2] R. C. Eberhart and J. Kennedy,”A new optimizer using particle swarm theory,” Proceedings of the 6th International Symposium on Micromachine and Human Science, Nagoya, Japan, 1995, pp. 39–43.
doi:10.1109/MHS.1995.494215

[3] Yi-Tung Kao, Erwie Zahara,”A hybrid genetic algorithm and particle swarm optimization for multimodal functions,” Applied Soft Computing, Vol.8(2), March 2008, pp. 849-857.
doi:10.1016/j.asoc.2007.07.002

[4] R.J. Kuo, S.Y. Hong, Y.C. Huang,”Integration of particle swarm optimization-based fuzzy neural network and artificial neural network for supplier selection,” Applied Mathematical Modelling, Vol.34(12), December 2010, pp.3976-3990.
doi:10.1016/j.apm.2010.03.033

[5] Serkan Kiranyaz, Turker Ince, Alper Yildirim, Moncef Gabbouj,”Evolutionary artificial neural networks by multi-dimensional particle swarm optimization,” Neural Networks, Vol.22(10), December 2009, pp.1448-1462.
doi:10.1016/j.neunet.2009.05.013
PMid:19556105

[6] Avishek Pal, J. Maiti, ”Development of a hybrid methodology for dimensionality reduction in Mahalanobis–Taguchi system using Mahalanobis distance and binary particle swarm optimization,” Expert Systems with Applications, Vol.37(2), March 2010, pp.1286-1293.

[7] W. Zhang, Y. T. Liu,”Multi-objective reactive power and voltage control based on fuzzy optimization strategy and fuzzy adaptive particle swarm,” International Journal of Electrical Power & Energy Systems, Vol.30(9), November 2008, pp.525-532.
doi:10.1016/j.ijepes.2008.04.005

[8] V.K. Patel, R.V. Rao,”Design optimization of shell-and-tube heat exchanger using particle swarm optimization technique,” Applied Thermal Engineering, Vol.30(11-12), August 2010, pp.1417-1425.
doi:10.1016/j.applthermaleng.2010.03.001

[9] P. Zhang, L. Kong and W. Z. Liu,”Real-time monitoring of laser welding based on multiple sensors,” Control and Decision Conference, 2008, CCDC 2008, Chinese 2-4 July 2008, pp. 1746-1748.
doi:10.1109/CCDC.2008.4597620

[10] Meneses, Anderson Alvarenga de Moura; Machado, Marcelo Dornellas; Schirru, Roberto,”Particle Swarm Optimization applied to the nuclear reload problem of a Pressurized Water Reactor,” Progress in Nuclear Energy, 2009, 51(2), pp. 319-326.

[11] X. L. Jin, L. H. Ma and T. J. Wu,”Convergence analysis of the particle swarm optimization based on stochastic processes,” Zidonghua Xuebao/Acta Automatica Sinica, v33, n12, December, 2007, pp.1263-1268.

[12] Monson C K and Sepp K D,”The Kalman Swarm-A New App roach to Particle Motion in Swarm Optimization,” Proceedings of the Genetic and Evolutionary Computation Conference. Springer, 2004, 140-150.

[13] P. S. Shelokar, Siarry Patrick and V. K. Jayaraman,”Particle swarm and ant colony algorithms hybridized for improved continuous optimization,” Applied Mathematics and Computation, May, 2007, 188(n1), pp. 129-142.
doi:10.1016/j.amc.2006.09.098

[14] B. Liu, L. Wang and Y. H. Jin,”Improved particle swarm optimization combined with chaos,” Chaos, Solitons and Fractals, Vol. 25, 2005, pp.1261–1271.
doi:10.1016/j.chaos.2004.11.095

[15] Zhihua Cui, Xingjuan Cai, Jianchao Zeng and Guoji Sun,”Particle swarm optimization with FUSS and RWS for high dimensional functions,” Applied Mathematics and Computation, Vol.205(1), 2008, pp. 98-108
doi:10.1016/j.amc.2008.05.147

[16] Zhihua Cui, Xingjuan Cai, Jianchao Zeng and Guoji Sun,”Apical-dominant particle swarm optimization,” Progress in Natural Science, Vol.18(12), 2008, pp. 1577-1582.
doi:10.1016/j.pnsc.2008.06.005

[17] S. L. Song, L. Kong, J. J. Cheng,”A Novel Stochastic Mutation Technique for Particle Swarm Optimization”. Dynamics of Continuous Discrete & Impulsive System, 2007, 14, pp.500–505.

[18] S. L. Song, L. Kong and P. Zhang. “Improved particle swarm optimization algorithm with accelerating factor,” Journal of Harbin Institute of Technology (New Series), January, 2007, 14(ns2), pp. 146-149.

[19] S. L. Song, L. Kong, P. Zhang and R. J. Su,”Particle Swarm Optimization Algorithm Based on Space Mutation and its Application,” 2009 International Conference on Intelligent Human- Machine Systems and Cybernetics. 26-27 August, 2009. vol.II, pp. 440-443.

[20] S. L. Song, L. Kong, Y. Gan and R. J. Su. “Hybrid particle swarm cooperative optimization algorithm and its application to MBC in alumina production,” Progress in Natural Science, Vol.18(11), 2008, pp.1423-1428 .
doi:10.1016/j.pnsc.2008.04.008

[21] Bilal Alatas, Erhan Akin, A. Bedri Ozer B.,”Chaos embedded particle swarm optimization algorithms,” Chaos, Solitons & Fractals, Vol.40(4), May 2009, pp.1715-1734.
doi:10.1016/j.chaos.2007.09.063

[22] J. S. Wu. Material Balance Computation in Alumina production process of Bayer and Series-to-parallel. Metallurgical Industry Press, Beijing, 2002. (in chinese)

[23] S. W. Bi. Alumina Production Process. Chemical Industry Press, Beijing, 2006. (in chinese)


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