Turbulent particle swarm optimization using fuzzy parameter tuning

Studies in Computational Intelligence

Volumn 203, Issue , 2009, Pages 291-312

  Abraham, Ajith ^a,b   Liu, Hongbo ^b,c  

^a NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

^b DALIAN MARITIME UNIVERSITY   (China)

^c DALIAN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 65549126697     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-01085-9_10     Document Type: Article

References (30)

1. Boeringer, D.W., Werner, D.H.: Particle swarm optimization versus genetic algorithms for phased array synthesis. IEEE Transactions on Antennas and Propagation 52(3), 771-779 (2004)
2. Cantu-Paz, E.: Efficient and Accurate Parallel Genetic Algorithms. Kluwer Academic Publishers, Dordrecht (2000)
3. Clerc, M., Kennedy, J.: The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation 6, 58-73 (2002)
4. Cordón, O., Herrera, F., Peregrin, A.: Applicability of the fuzzy operators in the design of fuzzy logic controllers. Fuzzy Sets and Systems 86, 15-41 (1997)
5. Du, F., Shi,W.K., Chen, L.Z., Deng, Y., Zhu, Z.F.: Infrared image segmentation with 2-D maximum entropy method based on particle swarm optimization. Pattern Recognition Letters 26, 597-603 (2005)
6. Eberhart, R.C., Shi, Y.H.: Comparison between genetic algorithms and particle swarm optimization. In: Proceedings of IEEE International Conference on Evolutionary Computation, pp. 611-616 (1998)
7. Eiben, A.E., Hinterding, R., Michalewicz, Z.: Parameter control in evolutionary algorithms. IEEE Transations on Evolutionary Computation 3(2), 124-141 (1999)
8. Feller, W.: An Introduction to Probability Theory and Its Application, 3rd edn. John Wiley & Sons, Chichester (1968)
9. Guo, C., Tang, H.: Global convergence properties of evolution stragtegies. Mathematica Numerica Sinica 23(1), 105-110 (2001)
10. He, R., Wang, Y., Wang, Q., Zhou, J., Hu, C.: An improved particle swarm optimization based on self-adaptive escape velocity. Journal of Software 16(12), 2036-2044 (2005)
11. Herrera, F., Lozano, M.: FuzzD adaptive genetic algorithms: design, taxonomy, and future directions. Soft Computing 7, 545-562 (2003)
12. Jiang, C.W., Etorre, B.: A hybrid method of chaotic particle swarm optimization and linear interior for reactive power optimisation. Mathematics and Computers in Simulation 68, 57-65 (2005)
13. Kennedy, J., Spears,W. M.: Aatching algorithms to problems: an experimental test of the particle swarm and some genetic algorithms on the multimodal problem generator. In: Proceedings of the IEEE International Conference on Evolutionary Computation, pp. 78-83 (1998)
14. Kennedy, J., Eberhart, R.: Swarm intelligence. Morgan Kaufmann Publishers, Inc., San Francisco (2001)
15. Lu, W.Z., Fan, H.Y., Lo, S.M.: Application of evolutionary neural network method in predicting pollutant levels in downtown area of Hong Kong. Neurocomputing 51, 387-400 (2003)
16. Mahfouf, M., Chen, M.Y., Linkens, D.A.: Adaptive weighted swarm optimization for multiobjective optimal design of alloy steels. In: Yao, X., Burke, E.K., Lozano, J.A., Smith, J., Merelo-Guervós, J.J., Bullinaria, J.A., Rowe, J.E., Tiňo, P., Kabán, A., Schwefel, H.-P. (eds.) PPSN 2004. LNCS, vol. 3242, pp. 762-771. Springer, Heidelberg (2004)
17. Mark, L., Shay, E.: A fuzzy-based lifetime extension of genetic algorithms. Fuzzy Sets and Systems 149, 131-147 (2005)
18. Orosz, J.E., Jacobson, S.H.: Analysis of static simulated annealing algorithms. Journal of Optimzation theory and Applications 115(1), 165-182 (2002)
19. Parsopoulos, K.E., Vrahatis, M.N.: Recent approaches to global optimization problems through particle swarm optimization. Natural Computing 1, 235-306 (2002)
20. Parsopoulos, K.E., Vrahatis, M.N.: On the computation of all global minimizers through particle swarm optimization. IEEE Transactions on Evolutionary Computation 8(3), 211-224 (2004)
21. Phan, H.V., Lech, M., Nguyen, T.D.: Registration of 3D range images using particle swarm optimization. In: Maher, M.J. (ed.) ASIAN 2004. LNCS, vol. 3321, pp. 223-235. Springer, Heidelberg (2004)
22. Schute, J.F., Groenwold, A.A.: A study of global optimization using particle swarms. Journal of Global Optimization 31, 93-108 (2005)
23. Shi, Y.H., Eberhart, R.C., Chen, Y.: Implementation of evolutionary fuzzy systems. IEEE Transactions on Fuzzy System 7(2), 109-119 (1999)
24. Shi, Y.H., Eberhart, R.C.: Fuzzy adaptive particle swarm optimization. In: Proceedings of IEEE International Conference on Evolutionary Computation, pp. 101-106 (2001)
25. Sousa, T., Silva, A., Neves, A.: Particle swarm based data mining algorithms for classification tasks. Parallel Computing 30, 767-783 (2004)
26. Ting, T., Rao, M., Loo, C.K., Ngu, S.S.: Solving unit commitment problem using hybrid particle swarm optimization. Journal of Heuristics 9, 507-520 (2003)
27. Trelea, I.C.: The particle swarm optiCization algorithm: convergence analysis and parameter selection. Information Processing Letters 85(6), 317-325 (2003)
28. Triki, E., Collette, Y., Siarry, P.: A theoretical study on the behavior of simulated annealing leading to a new cooling schedule. European Journal of Operational Research 166, 77-92 (2005)
29. van den Bergh, F.: An analysis of particle swarm optimizers, PhD thesis, University of Pretoria, South Africa (2002)
30. Yun, Y.S., Gen, M.: Performance analysis of adaptive genetic algorithms with fuzzy logic and heuristics. Fuzzy Optimization and Decision Making 2, 161-175 (2003)