Recent advances in particle swarm

Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004

Volumn 1, Issue , 2004, Pages 90-97

  Hu, Xiaohui ^a   Shi, Yuhui ^b   Eberhart, Russ ^c  

^a PURDUE UNIVERSITY   (United States)

^b EDS Embeded Systems Group   (United States)

^c Indiana University Purdue University Indianapolis   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DYNAMIC TRACKING; MULTIOBJECTIVE OPTIMIZATION; OPTIMIZATION PROBLEMS; PARTICLE SWARM OPTIMIZATION (PSO);

ALGORITHMS; COMPUTATIONAL METHODS; CONSTRAINT THEORY; NEURAL NETWORKS; PARAMETER ESTIMATION; PROBLEM SOLVING; STOCHASTIC PROGRAMMING;

OPTIMIZATION;

EID: 4344682502     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (49)

1. Eberhart, R. C. and Kennedy, J. A new optimizer using particle swarm theory. Proceedings of the Sixth International Symposium on Micromachine and Human Science, Nagoya, Japan, pp. 39-43, 1995
2. Kennedy, J. and Eberhart, R. C. Particle swarm optimization. Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ. pp. 1942-1948, 1995
3. Shi, Y. and Eberhart, R. C. A modified particle swarm optimizer. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 1998), Piscataway, NJ. pp. 69-73, 1998
4. El-Gallad, A. I., El-Hawary, M. E., and Sallam, A. A., "Swarming of intelligent particles for solving the nonlinear constrained optimization problem," Engineering Intelligent Systems for Electrical Engineering and Communications, vol. 9, no. 3, pp. 155-163, Sept.2001.
5. Hu, X. and Eberhart, R. C. Solving constrained nonlinear optimization problems with particle swarm optimization. Proceedings of the Sixth World Multiconference on Systemics, Cybernetics and Informatics 2002 (SCI 2002), Orlando, USA. 2002
6. Coello Coello, C. A. and Lechuga, M. S. MOPSO: a proposal for multiple objective particle swarm optimization. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002), Honolulu, Hawaii USA. 2002
7. Hu, X. and Eberhart, R. C. Multiobjective optimization using dynamic neighborhood particle swarm optimization. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002), Honolulu, Hawaii USA. pp. 1677-1681, 2002
8. Carlisle, A. and Dozier, G. Tracking changing extrema with adaptive particle swarm optimizer. Proceedings of the 5th Biannual World Automation Congress, 2002, Orlando, Florida, USA. pp. 265-270, 2002
9. Hu, X. and Eberhart, R. C. Adaptive particle swarm optimization: detection and response to dynamic systems. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002), Honolulu, Hawaii USA. pp. 1666-1670, 2002
10. Kennedy, J. and Mendes, R. Neighborhood topologies in fully-informed and best-of-neighborhood particle swarms. Proceedings of the 2003 IEEE International Workshop on Soft Computing in Industrial Applications 2003 (SMCia/03), pp. 45-50, 2003
11. Kennedy, J. and Mendes, R. Population structure and particle swarm performance. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002), Honolulu, Hawaii USA. 2002
12. Brits, R., Engelbrecht, A. P., and van den Bergh, F. Solving systems of unconstrained equations using particle swarm optimization. Proceedings of IEEE Conference on Systems, Man, and Cybernetics 2002 (SMC 2002), Hammamet, Tunisa, pp. 102-107, 2002
13. Peram, T., Veeramachaneni, K., and Mohan, C. K. Fitness-distance-ratio based particle swarm optimization. Proceedings of the IEEE Swarm Intelligence Symposium 2003 (SIS 2003), Indianapolis, Indiana, USA. pp. 174-181, 2003
14. Eberhart, R. C. and Shi, Y. Particle swarm optimization: developments, applications and resources. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2001), Seoul, Korea. 2001
15. Clerc, M. The swarm and the queen: towards a deterministic and adaptive particle swarm optimization. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 1999), pp. 1951-1957, 1999
16. Kennedy, J. Minds and cultures: particle swarm implications. Socially Intelligent Agents: Papers from the 1997 AAAI Fall Symposium, Menlo Park, CA. pp. 67-72, 1997
17. Zheng, Y., Ma, L., Zhang, L., and Qian, J. On the convergence analysis and parameter selection in particle swarm optimization. Proceedings of International Conference on Machine Learning and Cybernetics 2003, pp. 1802-1807, 2003
18. Kennedy, J. and Eberhart, R. C. A discrete binary version of the particle swarm algorithm. Proceedings of the World Multiconference on Systemics,Cybernetics and Informatics 1997, Piscataway, NJ. pp. 4104-4109, 1997
19. Chang, R. F. and Lu, C. N. Feeder reconfiguration for load factor improvement. Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference, pp. 980-984, 2002
20. Mohan, C. K. and Al-kazemi, B. Discrete particle swarm optimization. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001
21. Hu, X., Eberhart, R. C., and Shi, Y. Swarm intelligence for permutation optimization: a case study on n-queens problem. Proceedings of the IEEE Swarm Intelligence Symposium 2003 (SIS 2003), Indianapolis, Indiana, USA. pp. 243-246, 2003
22. Fieldsend, J. E. and Singh, S. A multi-objective algorithm based upon particle swarm optimisation, an efficient data structure and turbulence. Proceedings of the 2002 U.K. Workshop on Computational Intelligence, Birmingham, UK. pp. 37-44, 2002
23. Hu, X., Eberhart, R. C., and Shi, Y. Particle swarm with extended memory for multiobjective optimization. Proceedings of the IEEE Swarm Intelligence Symposium 2003 (SIS 2003), Indianapolis, Indiana, USA. pp. 193-197, 2003
24. Li, X. A non-dominated sorting particle swarm optimizer for multiobjective optimization. Lecture Notes in Computer Science (LNCS) No. 2723: Proceedings of the Genetic and Evolutionary Computation Conference 2003 (GECCO 2003), Chicago, IL, USA. pp. 37-48, 2003
25. Lu, H. Dynamic population strategy assisted particle swarm optimization in multiobjective evolutionary algorithm design. 2003. IEEE Neural Network Society. IEEE NNS Student Research Grants 2002 - Final Reports.
26. Moore, J. and Chapman, R. Application of particle swarm to multiobjective optimization. 1999. Department of Computer Science and Software Engineering, Auburn University.
27. Mostaghim, S. and Teich, J. r. Strategies for finding local guides in multi-objective particle swarm optimization (MOPSO). Proceedings of the IEEE Swarm Intelligence Symposium 2003 (SIS 2003), Indianapolis, Indiana, USA. pp. 26-33, 2003
28. Parsopoulos, K. E. and Vrahatis, M. N. Particle swarm optimization method in multiobjective problems. Proceedings of the ACM Symposium on Applied Computing 2002 (SAC 2002), pp. 603-607, 2002
29. Ray, T. and Liew, K. M., "A swarm metaphor for multiobjective design optimization," Engineering Optimization, vol. 34, no. 2, pp. 141-153, 2002.
30. Coello Coello, C. A., Toscano Pulido, G., and Salazar Lechuga, M. An extension of particle swarm optimization that can handle multiple objectives. Workshop on Multiple Objective Metaheuristics, Paris, France. 2002
31. Parsopoulos, K. E. and Vrahatis, M. N. Particle swarm optimization method for constrained optimization problems. Proceedings of the Euro-International Symposium on Computational Intelligence 2002, 2002
32. Ray, T. and Liew, K. M. A swarm with an effective information sharing mechanism for unconstrained and constrained single objective optimization problem. Proceedings of IEEE Congress on Evolutionary Computation (CEC 2001), Seoul, Korea, pp. 75-80, 2001
33. Eberhart, R. C. and Shi, Y. Tracking and optimizing dynamic systems with particle swarms. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2001), Seoul, Korea, pp. 94-97, 2001
34. Blackwell, T. M. Swarms in dynamic environments. Lecture Notes in Computer Science (LNCS) No. 2723: Proceedings of the Genetic and Evolutionary Computation Conference 2003 (GECCO 2003), Chicago, IL, USA. pp. 1-12, 2003
35. Eberhart, R. C. and Shi, Y. Evolving artificial neural networks. Proceedings of International Conference on Neural Networks and Brain, 1998, Beijing, P. R. China, pp. PL5-PL13, 1998
36. Engelbrecht, A. P. and Ismail, A., "Training product unit neural networks," Stability and Control: Theory and Applications, vol. 2, no. 1-2, pp. 59-74, 1999.
37. van den Bergh, F. and Engelbrecht, A. P., "Cooperative learning in neural networks using particle swarm optimizers," South African Computer Journal, vol. 26 pp. 84-90, 2000.
38. Zhang, C., Shao, H., and Li, Y. Particle swarm optimisation for evolving artificial neural network. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics 2000, pp. 2487-2490, 2000
39. Lu, W. Z., Fan, H.-Y., and Lo, S. M., "Application of evolutionary neural network method in predicting pollutant levels in downtown area of Hong Kong," Neurocomputing, vol. 51 pp. 387-400, 2003.
40. Settles, M., Rodebaugh, B., and Soule, T. Comparison of genetic algorithm and particle swarm optimizer when evolving a recurrent neural network. Lecture Notes in Computer Science (LNCS) No. 2723: Proceedings of the Genetic and Evolutionary Computation Conference 2003 (GECCO 2003), Chicago, IL, USA. pp. 151-152, 2003
41. He, Z., Wei, C., Yang, L., Gao, X., Yao, S., Eberhart, R. C., and Shi, Y. Extracting rules from fuzzy neural network by particle swarm optimization. Proceedings of IEEE Congress on Evolutionary Computation (CEC 1998), Anchorage, Alaska, USA. 1998
42. Shi, Y. and Eberhart, R. C. Particle swarm optimization with fuzzy adaptive inerita weight. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001
43. Xiao, X., Dow, E. R., Eberhart, R. C., Ben Miled, Z., and Oppelt, R. J. Gene clustering using self-organizing maps and particle swarm optimization. Proceedings of Second IEEE International Workshop on High Performance Computational Biology, Nice, France. 2003
44. Paquet, U. and Engelbrecht, A. P. Training support vector machines with particle swarms. Proceedings of the International Joint Conference on Neural Networks, 2003 (IJCNN 2003), pp. 1598, 2003
45. Rasmussen, T. K. and Krink, T., "Improved Hidden Markov Model training for multiple sequence alignment by a particle swarm optimization-evolutionary algorithm hybrid," Biosystems, vol. 72, no. 1-2, pp. 5-17, Nov.2003.
46. Abido, M. A. Particle swarm optimization for multimachine power system stabilizer design. Power Engineering Society Summer Meeting, pp. 1346-2001, 2001
47. Abido, M. A., "Optimal design of power system stabilizers using particle swarm optimization," IEEE Transactions on Energy Conversion, vol. 17, no. 3, pp. 406-413, Sept.2002.
48. Abido, M. A., "Optimal power flow using particle swarm optimization," International Journal of Electrical Power and Energy Systems, vol. 24, no. 7, pp. 563-571, 2002.
49. Agrafiotis, D. K. and Cedeno, W., "Feature selection for structure-activity correlation using binary particle swarms," Journal of Medicinal Chemistry, vol. 45, no. 5, pp. 1098-1107, Feb.2002.