Coevolutionary optimization algorithm with dynamic sub-population size

International Journal of Innovative Computing, Information and Control

Volumn 3, Issue 2, 2007, Pages 435-448

  Guo, Yuanping ^a   Cao, Xlanbin ^a   Yln, Hongzhang ^a   Tang, Zeying ^b  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

Coevolutionary optimization algorithm; Dynamic population size; Global asymptotic stability

Indexed keywords

EID: 63549120882     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (13)

1. Schneider, G., H. Wersing, B. Sendhoff and E. Korner, Evolutionary optimization of a hierarchical object recognition model, IEEE Transactions on Systems, Man and Cybernetics, Part B, vol.35. no.3, pp.426-437, 2005.
2. Im, C. H., H. K. Kim, H. K. Jung and K. Choi, A novel algorithm for multimodal function optimization based on evolution strategy, IEEE Transactions on Magnetics, vol.40, no.2, pp.1224-1227. 2004.
3. Mezura-Montes, E. and C. A. Coello, A simple multimembered evolution strategy to solve constrained optimization problems, IEEE Transactions on Evolutionary Computation, vol.9, no.l, pp.l-17, 2005.
4. Alpaydin, G., G. Dundar and S. Balkir, Evolution-based design of neural fuzzy networks using self-adapting genetic parameters, IEEE Transactions on Fuzzy Systems, vol.10, no.2, pp.211-221, 2002.
5. Rosin, C. and R. Belew, New methods for competitive coevolution, Evolutionary Computation, vol.5, no.l, pp.1-29, 1997.
6. Potter, M. and K. De Jong, Cooperative coevolution: An architecture for evolving coadapted sub-components, Evolutionary Computation, vol.8, no.l, pp.1-29, 2000.
7. Tan, K. C, T. H. Lee and E. F. Khor, Evolutionary algorithms with dynamic population size and local exploration for multiobjective optimization, IEEE Transactions on Evolutionary Computation, vol.5, no.6, pp.565-588, 2001.
8. Yen, G. G. and H. Lu, Dynamic multiobjective evolutionary algorithm: Adaptive cell-based rank and density estimation, IEEE Transactions on Evolutionary Computation, vol.7, no.3, pp.253-274, 2003.
9. Tahk, M. J. and B. C. Sun, Coevolutionary augmented Lagrangian methods for constrained optimization, IEEE Transactions on Evolutionary Computation, vol.4, no.2, pp.114-124, 2000.
10. Garcia-Pedrajas, N., C. Hervas-Martinez and D. Ortiz-Boyer, Cooperative coevolution of artificial neural network ensembles for pattern classification, IEEE Transactions on Evolutionary Computation, vol.9, no.3, pp.271-302, 2005.
11. Messerschmidt, L. and A. P. Engelbrecht, Learning to play games using a PSO-based competitive learning approach, IEEE Transactions on Evolutionary Computation, vol.8, no.3, pp.280-288, 2004.
12. Bongard, J. C. and H. Lipson, Nonlinear system identification using coevolution of models and tests, IEEE Transactions on Evolutionary Computation, vol.9, no.4, pp.361-384, 2005.
13. Marin, J. and R. V. Sole, Macroevolutionary algorithms: A new optimization method on fitness landscapes, IEEE Transactions on Evolutionary Computation, vol.3, no.4, pp.272-286, 1999.