Defining a standard for particle swarm optimization

Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007

Volumn , Issue , 2007, Pages 120-127

  Bratton, Daniel ^a   Kennedy, James ^b  

^a UNIVERSITY OF LONDON   (United Kingdom)

^b BUREAU OF LABOR STATISTICS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; HEURISTIC METHODS; NUMERICAL METHODS;

BASELINE; OPTIMIZATION COMMUNITY; PARTICLE SWARM OPTIMIZATION; STANDARD MEASURES;

GLOBAL OPTIMIZATION;

EID: 34548720461     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SIS.2007.368035     Document Type: Conference Paper

References (13)

1. J. Kennedy and R. Eberhart (1995). Particle Swarm Optimization. Proceedings of the 1995 IEEE International Conference on Neural Networks (Perth. Australia): IEEE Service Center, Piscataway, NJ, IV: pp 1942-1948.
2. R. Eberhart and J. Kennedy (1995). A New Optimizer using Particle Swarm Theory. Proceedings of the Sixth International Symposium on Micro Machine and Human Science (Nagoya, Japan): IEEE Service Center, Piscataway, NJ: pp 39-43.
3. J. Vesterstnøm and R. Thomsen (2004). A Comparative Study of Differential Evolution. Particle Swarm Optimization, and Evolutionary Algorithms on Numerical Benchmark Problems. Proceedings of the 2004 IEEE Congress on Evolutionary Computation. Volume 2, pp. 1980-1987
4. R. Eberhart and Y. Shi (1998). Comparison between Genetic Algorithms and Particle Swarm Optimization. EP '98: Proceedings of the 7th International Conference on Evolutionary Programming VII. pp. 611-616.
5. C. W. Reynolds (1987). Flocks. Herds, and Schools: A Distributed Behavioral Model. Computer Graphics, Volume 21, pp. 25-34.
6. F. Heppner and U. Grenander (1990). A stochastic nonlinear model for coordinated bird flocks. In S. Krasner, Ed., The Ubiquity of Chaos, AAAS Publications, Washington, DC:.
7. J. Kennedy and R. Mendes (2006). Neighborhood topologies in fully informed and best-of-neighborhood particle swarms. IEEE Transactions on Systems, Man, and Cybernetics. Part C: Applications and Reviews, Volume 36, Issue 4, pp. 515-519.
8. Y. Shi and R. Eberhart (1998). A Modified Particle Swarm Optimizer. Proceedings of the 1998 IEEE Congress on Evolutionary Computation, Anchorage. AK.
9. M. Clerc and J. Kennedy (2002). The particle swarm - explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation. 6(1): pp. 58-73.
10. R. Eberhart and Y. Shi (2000). Comparing Inertia Weights and Constriction Factors in Particle Swarm Optimization. Proceedings of the 2000 IEEE Congress on Evolutionary Computation, Volume 1, pp. 84-88.
11. C Monson and K. Seppi (2005). Exposing Origin-Seeking Bias in PSO. Proceedings of the 2005 Genetic and Evolutionary Computation Conference, pp 241-248.
12. D. K. Gehlhaar and D. B. Fogel (1996). Tuning evolutionary programming for conformationally exible molecular docking. Evolutionary Programming, pp. 419-429.
13. J. Jaccard and C. K. Wan (1996). LISREL approaches to interaction effects in multiple regression, Sage Publications, Thousand Oaks, CA.