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2009年1月9日星期五

Particle Swarm Optimization

Introduction

Particle swarm optimization (PSO) is a population based stochastic optimization technique developed by Dr. Eberhart and Dr. Kennedy in 1995, inspired by social behavior of bird flocking or fish schooling.

PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. 

Each particle keeps track of its coordinates in the problem space which are associated with the best solution (fitness) it has achieved so far. (The fitness value is also stored.) This value is called pbest. Another "best" value that is tracked by the particle swarm optimizer is the best value, obtained so far by any particle in the neighbors of the particle. This location is called lbest. when a particle takes all the population as its topological neighbors, the best value is a global best and is called gbest.

The particle swarm optimization concept consists of, at each time step, changing the velocity of (accelerating) each particle toward its pbest and lbest locations (local version of PSO). Acceleration is weighted by a random term, with separate random numbers being generated for acceleration toward pbest and lbest locations.

In past several years, PSO has been successfully applied in many research and application areas. It is demonstrated that PSO gets better results in a faster, cheaper way compared with other methods. 

Another reason that PSO is attractive is that there are few parameters to adjust. One version, with slight variations, works well in a wide variety of applications. Particle swarm optimization has been used for approaches that can be used across a wide range of applications, as well as for specific applications focused on a specific requirement.

PSO Bibliography

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This aim of this page is to provide an updated list of references for particle swarm researchers. If you wish your paper to be included, please send me an email

This list is constantly being updated. (last update: 2-20-2004)

    1995

  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

    1996

  3. Eberhart, R. C., Simpson, P. K., and Dobbins, R. W., Computational Intelligence PC tools, 1st ed. ed. Boston, MA: Academic press professional, 1996.

  4. Jenigiri, S. Comparative study of efficiency of genetic algorithms and particle swarm optimization technique to solve permutation problems. 1996

    1997

  5. 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

  6. Kennedy, J. The particle swarm: social adaptation of knowledge. Proceedings of IEEE International Conference on Evolutionary Computation, Indianapolis, IN. pp. 303-308, 1997

  7. 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

  8. Salerno, J. Using the particle swarm optimization technique to train a recurrent neural model. IEEE International Conference on Tools with Artificial Intelligence, 1997, pp. 45-49, 1997

    1998

  9. Angeline, P. J. Using selection to improve particle swarm optimization. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 1998), Anchorage, Alaska, USA. 1998

  10. Angeline, P. J. Evolutionary optimization versus particle swarm optimization: philosophy and performance differences. Evolutionary Programming VII: Proceedings of the Seventh Annual Conference on Evolutionary Programming, 1998

  11. Eberhart, R. C. and Shi, Y. Comparison between genetic algorithms and particle swarm optimization. Evolutionary Programming VII: Proceedings of the Seventh Annual Conference on Evolutionary Programming, San Diego, CA. 1998

  12. 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

  13. 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

  14. Kennedy, J. The behavior of particles. Evolutionary Programming VII: Proceedings of the Seventh Annual Conference on Evolutionary Programming, San Diego, CA. pp. 581-589, 1998

  15. Kennedy, J., "Thinking is social: experiments with the adaptive culture model," Journal of Conflict Resolution, vol. 42 pp. 56-76, 1998.

  16. Kennedy, J. and Spears, W. Matching algorithms to problems: an experimental test of the particle swarm and some genetic algorithms on thfe multimodal problem generator. Proceedings of IEEE Congress on Evolutionary Computation (CEC 1998), Anchorage, Alaska, USA. 1998

  17. Kennedy, J. Methods of agreement: inference among the eleMentals. Proceeding of the International Symposium on Intelligent Control 1998, Piscataway, NJ. pp. 883-887, 1998

  18. Ozcan, E. and Mohan, C. K. Analysis of a simple particle swarm optimization system. Intelligent Engineering Systems Through Artificial Neural Networks, pp. 253-258, 1998

  19. 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

  20. Shi, Y. and Eberhart, R. C. Parameter selection in particle swarm optimization. Evolutionary Programming VII: Proceedings of the Seventh Annual Conference on Evolutionary Programming, New York. pp. 591-600, 1998

    1999

  21. 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

  22. Eberhart, R. C. and Hu, X. Human tremor analysis using particle swarm optimization. Proceedings of the IEEE Congress on evolutionary computation (CEC 1999), Washington D.C. pp. 1927-1930, 1999

  23. 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.

  24. Fukuyama, Y., Takayama, S., Nakanishi, Y., and Yoshida, H. A particle swarm optimization for reactive power and voltage control in electric power systems. Proceedings of the Genetic and Evolutionary Computation Conference 1999 (GECCO 1999), Orlando, Florida, USA. pp. 1523-1528, 1999

  25. Ismail, A. and Engelbrecht, A. P. Training Product Units in Feedforward Neural Networks using Particle Swarm Optimization. Proceedings of the International Conference on Artificial Intelligence, Durban, South Africa. pp. 36-40, 1999

  26. Kennedy, J. Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance. Proceedings of IEEE Congress on Evolutionary Computation (CEC 1999), Piscataway, NJ. pp. 1931-1938, 1999

  27. Kennedy, J., "Minds and cultures: Particle swarm implications for beings in sociocognitive space," Adaptive Behavior, vol. 7, no. 3-4, pp. 269-288, 1999.

  28. Kennedy, J. Artificial sociocognition: Cultures of belief in populations of eleMentals. Proceedings of the 1999 International Conference on Virtual Worlds and Simulation, pp. 50-55, 1999

  29. Kennedy, J. and Eberhart, R. C., "The particle swarm: social adaptation in information processing systems.," in Corne, D., Dorigo, M., and Glover, F. (eds.) New Ideas in Optimization London, UK: McGraw-Hill, 1999.

  30. Moore, J. and Chapman, R. Application of particle swarm to multiobjective optimization. 1999. Department of Computer Science and Software Engineering, Auburn University.

  31. Ozcan, E. and Mohan, C. K. Particle swarm optimization: surfing the waves. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 1999), Washington, DC, USA. 1999

  32. Shi, Y. and Eberhart, R. C. Empirical study of particle swarm optimization. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 1999), Piscataway, NJ. pp. 1945-1950, 1999

  33. Suganthan, P. N. Particle swarm optimiser with neighbourhood operator. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 1999), Piscataway, NJ. pp. 1958-1962, 1999

  34. van den Bergh, F. Particle swarm weight initialization in multi-layer perceptron artificial neural networks. Development and Practice of Artificial Intelligence Techniques, Durban, South Africa. pp. 41-45, 1999

  35. Yoshida, H., Fukuyama, Y., Takayama, S., and Nakanishi, Y. A particle swarm optimization for reactive power and voltage control in electric power systems considering voltage security assessment. Proceedings of IEEE International Conference on Systems, Man, and Cybernetics 1999, pp. 502, 1999

  36. Yoshida, H., Kawata, K., Fukuyama, Y., and Nakanishi, Y. A particle swarm optimization for reactive power and voltage control considering voltage stability. Proceedings of the International Conference on Intelligent System Application to Power System, Rio de Janeiro, Brazil. pp. 117-121, 1999

    2000

  37. Carlisle, A. and Dozier, G. Adapting particle swarm optimization to dynamic environments. Proceedings of International Conference on Artificial Intelligence (ICAI 2000), Las Vegas, Nevada, USA. pp. 429-434, 2000

  38. Dozier, G., Homaifar, A., and Tunstel, E. Neuro-evolutionary path planning. Proceedings of the Fifth Joint Conference on Information Sciences, pp. 1027-1030, 2000

  39. Eberhart, R. C. and Shi, Y. Comparing inertia weigthts and constriction factors in particle swarm optimization. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2000), San Diego, CA. pp. 84-88, 2000

  40. Fourie, P. C. and Groenwold, A. A. Particle swarms in size and shape optimization. Proceedings of the International Workshop on Multidisciplinary Design Optimization, Pretoria, South Africa. pp. 97-106, 2000

  41. Ioan, D., Ciuprina, G., and Munteanu, I. Intelligent-particle swarm optimization. Proceedings of 6th International Workshop on Optimization and Inverse Problems in Electromagnetism (OIPE 2000), Torino, Italy. 2000

  42. Ismail, A. and Engelbrecht, A. P. Global optimization algorithms for training product unit neural networks. Proceedings of IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2000), pp. 132-137, 2000

  43. Kennedy, J. Human and computer learning together in the exteriorized particle swarm. Socially Intelligent Agents: The Human in the Loop (papers from the 2000 Fall Symposium), 2000

  44. Kennedy, J. Stereotyping: improving particle swarm performance with cluster analysis. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2000), San Diego, CA. pp. 1507-1512, 2000

  45. Kennedy, J. Sociocognitive computation: a new interdisciplinary convergence. Proceedings of the Virtual Worlds and Simulation Conference, pp. 165-170, 2000

  46. Naka, S., Genji, T., Yura, T., Fukuyama, Y., and Hayashi, N. Distribution state estimation considering nonlinear characteristics of practical equipment using hybrid particle swarm optimization. International Conference on Power System Technology 2000., pp. 1083-1088, 2000

  47. Peng, J., Chen, Y., and Eberhart, R. C. Battery pack state of charge estimator design using computational intelligence approaches. The Fifteenth Annual Battery Conference on Applications and Advances 2000., pp. 173-177, 2000

  48. Shi, Y. and Eberhart, R. C. Experimental study of particle swarm optimization. Proceedings of the World Multiconference on Systemics,Cybernetics and Informatics 2000, Orlando, FL. 2000

  49. 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.

  50. Wegley, C., Eusuff, M., and Lansey, K. Determining pump operations using particle swarm optimization. Proceedings of the Joint Conference on Water Resources Engineering and Water Resources Planning and Management 2000, Minneapolis, Minnesota. 2000

  51. Yoshida, H., Kawata, K., Fukuyama, Y., Takayama, S., and Nakanishi, Y., "A particle swarm optimization for reactive power and voltage control considering voltage security assessment," IEEE Transactions on Power Systems, vol. 15, no. 4, pp. 1232-1239, Nov.2000.

  52. Zhang, C. and Shao, H. An ANN's evolved by a new evolutionary system and its application. Proceedings of the 39th IEEE Conference on Decision and Control, pp. 3562-3563, 2000

  53. Zhang, C., Li, Y., and Shao, H. A new evolved artificial neural network and its application. Proceedings of the 3rd World Congress on Intelligent Control and Automation, Hefei, China. pp. 1065-1068, 2000

  54. 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

    2001

  55. Abido, M. A. Particle swarm optimization for multimachine power system stabilizer design. Power Engineering Society Summer Meeting, pp. 1346-2001, 2001

  56. Carlisle, A. and Dozier, G. Tracking changing extrema with particle swarm optimizer. Technical Report CSSE01-08. 2001. Auburn University.

  57. Carlisle, A. and Dozier, G. An off-the-shelf PSO. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001

  58. Cockshott, A. R. and Hartman, B. E., "Improving the fermentation medium for Echinocandin B production part II: Particle swarm optimization," Process Biochemistry, vol. 36 pp. 661-669, 2001.

  59. Coello Coello, C. A. and Lechuga, M. S. MOPSO: a proposal for multiple objective particle swarm optimization. Technical Report EVOCINV-01-2001. 2001. Mexico, Evolutionary Computation Group at CINVESTAV, Sección de Computación, Departamento de Ingeniería Eléctrica, CINVESTAV-IPN.

  60. 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

  61. 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

  62. El-Gallad, A. I., El-Hawary, M. E., Sallam, A. A., and Kalas, A. Swarm intelligence for hybrid cost dispatch problem. Canadian Conference on Electrical and Computer Engineering, 2001, pp. 753-757, 2001

  63. 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.

  64. El-Gallad, A. I., El-Hawary, M. E., Sallam, A. A., and Kalas, A. Swarm-intelligently trained neural network for power transformer protection. Canadian Conference on Electrical and Computer Engineering, 2001, pp. 265-269, 2001

  65. Fan, H.-Y. and Shi, Y. Study on Vmax of particle swarm optimization. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001

  66. Fourie, P. C. and Groenwold, A. A. Particle swarms in topology optimization. Extended Abstracts of the Fourth World Congress of Structural and Multidisciplinary Optimization, Dalian, China. pp. 52-53, 2001

  67. Fukuyama, Y. and Yoshida, H. A particle swarm optimization for reactive power and voltage control in electric power systems. Proceedigns of the IEEE Congress on Evolutionary Computation (CEC 2001), Seoul, Korea. 2001

  68. Fukuyama, Y. State estimation and optimal setting of voltage regulator in distribution systems. IEEE Power Engineering Society Winter Meeting, 2001, pp. 930-935, 2001

  69. Hendtlass, T. and Randall, M. A survey of ant colony and particle swarm meta-heuristics and their application to discrete optimisation problems. Proceedings of The Inaugural Workshop on Artificial Life (AL 2001), pp. 15-25, 2001

  70. Hendtlass, T. A combined swarm differential evolution algorithm for optimization problems. Lecture Notes in Computer Science(LNCS) No.2070: Proceedings of the 14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2001), Budapest, Hungary. pp. 11-18, 2001

  71. Hu, X. and Eberhart, R. C. Tracking dynamic systems with PSO: where's the cheese? Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001

  72. Kennedy, J. Out of the computer, into the world: externalizing the particle swarm. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001

  73. Kennedy, J. Minimal science in a virtual paradigm. Proceedings of the Virtual Worlds and Simulation Conference, pp. 207-212, 2001

  74. Kennedy, J., Eberhart, R. C., and Shi, Y., Swarm intelligence San Francisco: Morgan Kaufmann Publishers, 2001.

  75. Laskari, E. C., Parsopoulos, K. E., and Vrahatis, M. N. Utilizing evolutionary operators in global optimization with dynamic search trajectories. International Conference on Numerial algorithms, Marrakesh, Morocco. 2001

  76. Liu, Y., Zhang, H., Chu, X., and Liu, Y. Particle swarm optimization for fault state power supply reliability enhancement. International Conference on Intelligent System Application to Power Systems (ISAP2001), Budapest, Hungary. 2001

  77. Løvbjerg, M., Rasmussen, T. K., and Krink, T. Hybrid particle swarm optimiser with breeding and subpopulations. Proceedings of the Genetic and Evolutionary Computation Conference 2001 (GECCO 2001), 2001

  78. Mitchell, M. and Forrest, S., "Genetic algorithms and artificial life," Artificial Life, vol. 1, no. 3, pp. 267-289, 2001.

  79. Mohan, C. K. and Al-kazemi, B. Discrete particle swarm optimization. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001

  80. Naka, S., Genji, T., Yura, T., and Fukuyama, Y. Practical distribution state estimation using hybrid particle swarm optimization. IEEE Power Engineering Society Winter Meeting, 2001, Columbus, Ohio, USA. pp. 815-820, 2001

  81. Parsopoulos, K. E., Plagianakos, V. P., Magoulas, G. D., and Vrahatis, M. N. Improving particle swarm optimizer by function "stretching". Advances in Convex Analysis and Global Optimization, pp. 445-457, 2001

  82. Parsopoulos, K. E., Plagianakos, V. P., Magoulas, G. D., and Vrahatis, M. N. Stretching technique for obtaining global minimizers through particle swarm optimization. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001

  83. Parsopoulos, K. E., Plagianakos, V. P., Magoulas, G. D., and Vrahatis, M. N., "Objective function "stretching" to alleviate convergence to local minima," Nonlinear Analysis, Theory, Methods and Applications, vol. 47, no. 5, pp. 3419-3424, 2001.

  84. Parsopoulos, K. E. and Vrahatis, M. N. Particle swarm optimizer in noisy and continuously changing environments. Proceeding of the IASTED International Conference on Artificial Intelligence and Soft Computing (ASC 2001), Cancun, Mexico. pp. 289-294, 2001

  85. Parsopoulos, K. E. and Vrahatis, M. N. Modification of the particle swarm optimizer for locating all the global minima. Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA 2001), Prague, Czech Republic. pp. 324-327, 2001

  86. Parsopoulos, K. E., Laskari, E. C., and Vrahatis, M. N. Solving L1 norm errors-in-variables problems using particle swarm optimizer. Proceeding of the IASTED International Conference on Artificial Intelligence and Soft Computing (ASC 2001), Cancun, Mexico. pp. 185-190, 2001

  87. Parsopoulos, K. E. and Vrahatis, M. N. Particle swarm optimization for imprecise problems. Proceedings of the 5th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Technology, Corfu, Greece. 2001

  88. 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

  89. Salman, A., Imtiaz, A., and Al-Madani, S. Particle swarm optimization for task assignment problem. IASTED International Conference on Artificial Intelligence and Applications (AIA 2001), Marbella, Spain. 2001

  90. Salman, A., Imtiaz, A., and Al-Madani, S. Discrete particle swarm optimization for heterogeneous task assignment problem. Proceedings of World Multiconference on Systemics, Cybernetics and Informatics Cybernetics And Informatics (SCI 2001), 2001

  91. Secrest, B. R. and Lamont, G. B. Communication in particle swarm optimization illustrated by the traveling salesman problem. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001

  92. Secrest, Barry R., "Traveling salesman problem for surveillance mission using particle swarm optimization." Master's thesis School of Engineering and Management of the Air Force Institue of Technology, Air University, 2001.

  93. 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

  94. Shi, Y. and Eberhart, R. C. Fuzzy adaptive particle swarm optimization. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2001), Seoul, Korea. 2001

  95. Tandon, Vipul, "Closing the gap between CAD/CAM and optimized CNC end milling." Master's thesis Purdue School of Engineering and Technology, Indiana University Purdue University Indianapolis, 2001.

  96. van den Bergh, F. and Engelbrecht, A. P. Training product unit networks using cooperative particle swarm optimisers. Proceedings of INNS-IEEE International Joint Conference on Neural Networks 2001, Washington DC, USA. 2001

  97. van den Bergh, F. and Engelbrecht, A. P. Effects of swarm size on cooperative particle swarm optimisers. Proceedings of the Genetic and Evoluationary Computation Conference 2001, San Francisco, USA. 2001

  98. Voss, J. L. Minds, cultures, the environment and altruism: a meta model using particle swarm - agent based modeling. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. 2001

  99. Voss, M. S. and Feng, X. Emergent system identification using particle swarm optimization. Complex Adaptive Structures, Hutchinson Island, Florida, USA. 2001

  100. Voss, M. S. and Feng, X. ARMA model selection using particle swarm optimization and AIC criteria. 15th Triennial World Congress, Barcelona, Spain. 2001

  101. Yoshida, H., Kawata, K., Fukuyama, Y., Takayama, S., and Nakanishi, Y. A particle swarm optimization for reactive power and voltage control considering voltage security assessment. Proceedings of Power Engineering Society Winter Meeting, 2001, pp. 498, 2001

  102. Zhang, F. and Xue, D. An optimal concurrent design model using distributed product development life-cycle databases. The Sixth International Conference on Computer Supported Cooperative Work in Design, pp. 273-278, 2001

  103. Zhang, F. and Xue, D., "Optimal concurrent design based upon distributed product development life-cycle modeling," Robotics and Computer-Integrated Manufacturing, vol. 17, no. 6, pp. 469-486, 2001.

    2002

  104. 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.

  105. 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.

  106. 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.

  107. Al-kazemi, B. and Mohan, C. K. Training feedforward neural networks using multi-phase particle swarm optimization. Proceedings of the 9th International Conference on Neural Information Processing (ICONIP 2002), Singapore. 2002

  108. Al-kazemi, B. and Mohan, C. K. Multi-phase generalization of the particle swarm optimization algorithm. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002), Honolulu, Hawaii USA. 2002

  109. Al-kazemi, B. and Mohan, C. K. Multi-phase discrete particle swarm optimiziation. Proceeding of Fourth International Workshop on Frontiers in Evolutionary Algorithms (FEA 2002), 2002

  110. Beielstein, T., Parsopoulos, K. E., and Vrahatis, M. N. Tuning PSO parameters through sensitivity analysis. Technical Report, Reihe Computational Intelligence CI 124/02. 2002. Collaborative Research Center (Sonderforschungsbereich) Department of Computer Science, University of Dortmund.

  111. Blackwell, T. M. and Bentley, P. J. Improvised music with swarms. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002), Honolulu, Hawaii USA. 2002

  112. Blackwell, T. M. and Bentley, P. J. Dynamic search with charged swarms. Proceedings of the Genetic and Evolutionary Computation Conference 2002 (GECCO 2002), New York, NY. USA. pp. 19-26, 2002

  113. Blackwell, T. M. and Bentley, P. J. Don't push me! collision-avoiding swarms. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002), Honolulu, Hawaii USA. 2002

  114. Braendler, D. and Hendtlass, T. The suitability of particle swarm optimisation for training neural hardware. Lecture Notes in Computer Science(LNCS) No.2358: Proceedings of the 15th International Conference on Industrial and Engineering, Applications of Artificial Intelligence and Expert Systems 2002 (IEA/AIE 2002), Cairns, Australia. 2002

  115. Brandstatter, B. and Baumgartner, U., "Particle swarm optimization-mass-spring system analogon," IEEE Transactions on Magnetics, vol. 38, no. 2, pp. 997-1000, Mar.2002.

  116. 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

  117. Brits, R., Engelbrecht, A. P., and van den Bergh, F. A niching particle swarm optimizer. Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution and Learning 2002 (SEAL 2002), Singapore. pp. 692-696, 2002

  118. Carlisle, Anthony, "Applying the particle swarm optimizer to non-stationary environments." Auburn University, Auburn Alabama, 2002.

  119. 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

  120. Cedeno, W. and Agrafiotis, D. K., "Combining particle swarms and k-nearest neighbors for the development of quantitative structure-activity relationships," International Journal of Computer Research, 2002.

  121. 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

  122. Ciuprina, G., Ioan, D., and Munteanu, I., "Use of intelligent-particle swarm optimization in electromagnetics," IEEE Transactions on Magnetics, vol. 38, no. 2, pp. 1037-1040, Mar.2002.

  123. Clerc, M., "L'optimisation par essaim particulaire. Principes, modèles et usages," Hermès, Technique et science informatiques, vol. 21 pp. 941-964, 2002.

  124. Clerc, M. and Kennedy, J., "The particle swarm-explosion, stability, and convergence in a multidimensional complex space," IEEE Transactions on Evolutionary Computation, vol. 6, no. 1, pp. 58-73, 2002.

  125. Coelho, J. o. P., Oliveira, P. M., and Cunha, J. B. Greenhouse air temperature control using the particle swarm optimisation algorithm. Proceedings of 15th Triennial World Congress of the International Federation of Automatic Control (IFAC 2002), Barcelona, Spain. 2002

  126. 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

  127. Coello Coello, C. A., Luna, E. H. n., and Aguirre, A. H. n. Use of particle swarm optimization to design combinational logic circuits. Technical Report EVOCINV-04-2002. 2002. Mexico, Evolutionary Computation Group at CINVESTAV, Sección de Computación, Departamento de Ingeniería Eléctrica, CINVESTAV-IPN.

  128. Coello Coello, C. A., Toscano Pulido, G., and Salazar Lechuga, M. Handling multiple objectives with particle swarm optimization. Technical Report EVOCINV-02-2002. 2002. Mexico, Evolutionary Computation Group at CINVESTAV, Sección de Computación, Departamento de Ingeniería Eléctrica, CINVESTAV-IPN.

  129. 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

  130. Conradie, A., Miikkulainen, R., and Aldrich, C. Intelligent process control utilising symbiotic memetic neuro-evolution. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002), Hawaii, USA. pp. 623-628, 2002

  131. Conradie, A., Miikkulainen, R., and Aldrich, C. Adaptive control utilizing neural swarming. Proceedings of the Genetic and Evolutionary Computation Conference 2002 (GECCO 2002), New York, NY. 2002

  132. Crepinsek, M., Mernik, M., and Zumer, V. Using flocks for solving numerical optimization problems. Proceedings of the 24th International Conference on Information Technology Interfaces (ITI 2002), pp. 395-400, 2002

  133. El-Gallad, A. I., El-Hawary, M. E., Sallam, A. A., and Kalas, A. Particle swarm optimizer for constrained economic dispatch with prohibited operating zones. Canadian Conference on Electrical and Computer Engineering, 2002, pp. 78-81, 2002

  134. El-Gallad, A. I., El-Hawary, M. E., Sallam, A. A., and Kalas, A. Enhancing the particle swarm optimizer via proper parameters selection. Canadian Conference on Electrical and Computer Engineering, 2002, pp. 792-797, 2002

  135. El-Gallad, A. I., El-Hawary, M. E., Phillips, W., and Sallam, A. A. PSO-based neural network for dynamic bandwidth re-allocation. Proceedings of Large Engineering Systems Conference on Power Engineering 2002 (LESCOPE 2002), pp. 98-102, 2002

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    2004

  310. Adly, A. A. and Abd-El-Hafiz, S. K., "Field computation in non-linear magnetic media using particle swarm optimization," Journal of Magnetism and Magnetic Materials, vol. In Press, Uncorrected Proof 2004.

  311. Clerc, M., "Discrete Particle Swarm Optimization," New Optimization Techniques in Engineering Springer-Verlag, 2004.

  312. Kannan, S., Slochanal, S. M. R., Subbaraj, P., and Padhy, N. P., "Application of particle swarm optimization technique and its variants to generation expansion planning problem," Electric Power Systems Research, vol. In Press, Corrected Proof 2004.

  313. Onwubolu, G. C. and Clerc, M., "Optimal path for automated drilling operations by a new heuristic approach using particle swarm optimization," International Journal of Production Research, vol. 4 pp. 473-491, 2004.

  314. Venter, G. and Sobieszczanski-Sobieski, J., "Multidisciplinary optimization of a transport aircraft wing using particle swarm optimization," Structural and Multidisciplinary Optimization, pp. preprint, 2004.

  315. Yin, P., "A discrete particle swarm algorithm for optimal polygonal approximation of digital curves," Journal of Visual Communication and Image Representation, vol. In Press, Corrected Proof 2004.

  316. Zhang, X., Yu, L., Zheng, Y., Shen, Y., Zhou, G., Chen, L., Xi, L., Yuan, T., Zhang, J., and Yang, B., "Two-stage adaptive PMD compensation in a 10 Gbit/s optical communication system using particle swarm optimization algorithm," Optics Communications, vol. 231, no. 1-6, pp. 233-242, Jan.2004. 

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