Enhanced particle swarm optimization based on principal component analysis and line search

Applied Mathematics and Computation

Volumn 229, Issue , 2014, Pages 440-456

  Zhao, Xinchao ^a   Lin, Wenqiao ^a   Zhang, Qingfu ^b  

^a BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^b UNIVERSITY OF ESSEX   (United Kingdom)

Author keywords

Information accumulation; Line search; Particle swarm optimization; Principal component analysis; Swarm intelligence; Velocity diversity

Indexed keywords

PRINCIPAL COMPONENT ANALYSIS; SWARM INTELLIGENCE; VELOCITY;

ENHANCED PARTICLE SWARM OPTIMIZATION; HEURISTIC INFORMATION; INFORMATION ACCUMULATION; LINE SEARCHES; LINEAR COMBINATIONS; PRINCIPAL COMPONENTS; STATE-OF-THE-ART ALGORITHMS; VELOCITY INFORMATION;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 84892775031     PISSN: 00963003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amc.2013.12.068     Document Type: Article

References (38)

1. J. Holland Adaptation in Natural and Artificial Systems 1992 MIT Press Cambridge, MA
2. D. Karaboga, and B. Akay A comparative study of artificial bee colony algorithm Appl. Math. Comput. 214 1 2009 108 132
3. S. Das, and P.N. Suganthan Differential evolution: a survey of the state-of-the-art IEEE Trans. Evol. Comput. 15 1 2011 4 31
4. B.C. Mohan, and R. Baskaran A survey: ant colony optimization based recent research and implementation on several engineering domain Expert Syst. Appl. 39 4 2012 4618 4627
5. R. Poli, J. Kennedy, and T. Blackwell Particle swarm optimization - an overview Swarm Intell. 1 1 2007 33 57
6. M. El-Abd An improved global-best harmony search algorithm Appl. Math. Comput. 222 2013 94 106
7. A. Banks, J. Vincent, and C. Anyakoha A review of particle swarm optimization, part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications Nat. Comput. 7 1 2008 109 124
8. J. Kennedy, R.C. Eberhart, Particle swarm optimization, in: Proceedings of the 1995 IEEE International Conference on Neural Networks, 1995, vol. 4, pp. 1942-1948.
9. J.J. Liang, A.K. Qin, P.N. Suganthan, and S. Baskar Comprehensive learning particle swarm optimizer for global optimization of multimodal functions IEEE Trans. Evol. Comput. 10 3 2006 281 295
10. H. Wang, Z.J. Wu, and Y. Liu Enhancing particle swarm optimization using generalized opposition-based learning Inf. Sci. 181 2011 4699 4714
11. H. Cho, D. Kim, F. Olivera, and S.D. Guikema Enhanced speciation in particle swarm optimization for multi-modal problems Eur. J. Oper. Res. 213 2011 15 23
12. A. Nickabadi, M.M. Ebadzadeh, and R. Safabakhsh A novel particle swarm optimization algorithm with adaptive inertia weight Appl. Soft Comput. 11 2011 3658 3670
13. Z.H. Zhan, J. Zhang, Y. Li, and Y.H. Shi Orthogonal learning particle swarm optimization IEEE Trans. Evol. Comput. 15 2011 832 847
14. X.C. Zhao, B.Q. Song, and P.Y. Huang et al. An improved discrete immune optimization algorithm based on PSO for QoS-driven web service composition Appl. Soft Comput. 12 8 2012 2208 2216
15. M.S. Voss Principal component particle swarm optimization Proceedings of the 2005 IEEE Swarm Intelligence Symposium 2005 IEEE Press 8 10
16. H.X. Gao Applied Multivariate Statistical Analysis 2005 Peking University Press
17. A.S. Lodge Body tensor fields in continuum mechanics with applications to polymer theology 1974 Academic Press
18. K. Lewin Field Theory in Social Science 1951 Harper & Brothers
19. H.-G. Beyer, and H.-P. Schwefel Evolution strategies - a comprehensive introduction Nat. Comput. 1 1 2002 3 52
20. J. Pahasa, and I. Ngamroo PSO based kernel principal component analysis and multi-class support vector machine for power quality problem classification International Journal of Innovative Computing, Information and Control 8 3(A) 2012 1523 1539
21. W. Chu, X.G. Gao, S. Sorooshian, Fortify particle swam optimizer (PSO) with principal components analysis, in: 2011 IEEE Congress on Evolutionary Computation, pp. 1644-1648, 2011.
22. A. Kuznetsova, G. Pons-Moll, B. Rosenhahn, PCA-enhanced stochastic optimization methods, in: DAGM/OAGM Symposium 2012, LNCS 7476,pp. 377-386, 2012.
23. Y.X. Wang, and H.X. Sun Probability Theory and Stochastic Processes 2003 Beijing University of Posts and Telecommunications Press
24. L.E. Johnson, R.D. Riess, and J.T. Arnold Introduction to Linear Algebra 2000 Prentice-Hall Inc.
25. J. Jahn Introduction to the Theory of Nonlinear Optimization third ed. 2007 Springer
26. S. Cheng, Y. Shi, and Q. Qin A study of normalized population diversity in particle swarm optimization Int. J. Swarm Intell. Res. 4 1 2013 1 34
27. M. Pant, T. Radha, V.P. Singh, A simple diversity guided particle swarm optimization, in: IEEE Congress on Evolutionary Computation, pp. 3294-3299, 2007.
28. B. Lacevic, and E. Amaldi Ectropy of diversity measures for populations in Euclidean space Inf. Sci. 181 2011 2316 2339
29. G. Corriveau, R. Guilbault, A. Tahan, and R. Sabourin Review and study of genotypic diversity measures for real-coded representations IEEE Trans. Evol. Comput. 16 5 2012 695 710
30. X.C. Zhao A perturbed particle swarm algorithm for numerical optimization Appl. Soft Comput. 10 1 2010 119 124
31. M. Lovbjerg, T.K. Rasmussen, T. Krink, Hybrid particle swarm optimizer with breeding and subpopulations, in: Proceedings of the Genetic and Evolutionary Computation Conference, Morgan Kaufmann, 2001.
32. J. Kennedy, R.C. Eberhar, and Y. Shi Swarm Intelligence 2001 Morgan Kaufman San Francesco, CA
33. Y. Shi, and R.C. Eberhart Fuzzy adaptive particle swarm optimization Proceedings of the 2001 Congress on Evolutionary Computatio 2001 IEEE Press 101 106
34. X.F. Xie, W.J. Zhang, Z.L. Yang, Hybrid particle swarm optimizer with mass extinction, in: Int. Conf. on Communication, Circuits and Systems, pp. 1170-1173, 2002.
35. P.N. Suganthan, N. Hansen, J.J. Liang, K. Deb, Y.-P. Chen, A, Auger, S. Tiwari, Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization, in: Nanyang Technol. Univ., Singapore, 2005.
36. C. Garcia-Martinez, M. Lozano, F. Herrera, D. Molina, and A.M. Sanchez Global and local real-coded genetic algorithms based on parent-centric crossover operators Eur. J. Oper. Res. 185 3 2008 1088 1113
37. Y. Wang, Z.X. Cai, and Q.F. Zhang Differential evolution with composite trial vector generation strategies and control parameters IEEE Trans. Evol. Comput. 15 1 2011 55 66
38. A. Nickabadi, M.M. Ebadzadeh, and R. Safabakhsh A novel particle swarm optimization algorithm with adaptive inertia weight Appl. Soft Comput. 11 2011 3658 3670