Trusted evolutionary algorithm

2006 IEEE Congress on Evolutionary Computation, CEC 2006

Volumn , Issue , 2006, Pages 149-156

  Lim, Dudy ^b   Ong, Yew Soon ^a,b   Jin, Yaochu ^a,c   Sendhoff, Bernhard ^a,c  

^a IEEE

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c HONDA RESEARCH INSTITUTE EUROPE GMBH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL EFFICIENCY; CONVERGENCE OF NUMERICAL METHODS; MATHEMATICAL MODELS; OPTIMIZATION; RANDOM PROCESSES;

NEAR-OPTIMUM SOLUTIONS; STOCHASTIC OPTIMIZATION; TRUST REGION FRAMEWORK (TRF);

EVOLUTIONARY ALGORITHMS;

EID: 34547293252     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (28)

1. M.K. Karakasis, A.P. Giotis, and K.C. Giannakoglou, "Inexact information aided, low-cost, distributed genetic algorithms for aerodynamic shape optimization", International Journal for Numerical Methods in Fluids, vol. 43, pp. 1149-1166, 2003.
2. P. Hajela, J. Lee, " Genetic algorithms in multidisciplinary rotor blade design", In Proceedings of 36th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Material Conference, New Orleans, pp. 2187-2197, 1995.
3. H. Fang, P. Ross, and D. Corne, "A Promising Genetic Algorithm Approach to Job-shop Scheduling, Rescheduling and open-shop scheduling problems", Proceedings of the 5th International Conference on Genetic Algorithms, ICGA-93. Morgan Kaufmann, 1993.
4. CG. Johnson and J.J.R. Caldalda, "Introduction: Genetic Algorithms in Visual Art and Music", Leonardo - Volume 35, Number 2, April 2002, pp. 175-184.
5. P.B. Nair, A.J. Keane, "Passive Vibration Suppression of Flexible Space Structures via Optimal Geometric Redesign", AIAA Journal 39(7), pp. 1338-1346, 2001.
6. F.S. Lesh, "Multi-dimensional least-square polynomial curve fitting", Communications of ACM, vol. 2, no. 9, pp. 29-30, 1959.
7. Z. Zhou, Y.S. Ong, M.H. Nguyen, D. Lim, "A Study on Polynomial Regression and Gaussian Process Global Surrogate Model in Hierarchical Surrogate-Assisted Evolutionary Algorithm", IEEE Congress on Evolutionary Computation, Edinburgh, United Kingdom, September 2-5, 2005.
8. A.A. Guinta and L. Watson, "A comparison of approximation modelling techniques: polynomial versus interpolating models", in Proc. the 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, AIAA-98-4758, St. Louis, MO, USA, Sept. 1998.
9. L. Gräning, Y. Jin, B. Sendhoff, "Efficient Evolutionary Optimization Using Individual-based Evolution Control and Neural Networks: A Comparative Study", Proceeding of European Symposium on Artificial Neural Networks (ESANN), Bruges (Belgium), 27-29 April 2005.
10. L. Willmes, T. Back, Y. Jin, and B. Sendhoff, "Comparing Neural Networks and Kriging for Fitness Approximation in Evolutionary Optimization", In Proceedings of IEEE Congress on Evolutionary Computation, pages 663-670, 2003.
11. A. Ratle, "Kriging as a surrogate fitness landscape in evolutionary optimization", Artificial Intelligence for Engineering Design Analysis and Manufacturing, vol. 15, no. 1, pp. 37-49, 2001.
12. D. Buche, N.N. Schraudolph, and P. Koumoutsakos, "Accelerating evolutionary algorithms with gaussian process fitness function models", IEEE Transactions on Systems, Man, and Cybernetics part C, 2004.
13. Z. Zhou, Y.S. Ong, P.B. Nair, A.J. Keane, and K.Y. Lum, "Combining Global and Local Surrogate Models to Accelerate Evolutionary Optimization", IEEE Transactions on Systems, Man and Cybernetics (SMC), part C, In press, expected July 2006.
14. M.A. El-Beltagy, P.B. Nair, A.J. Keane, "Metamodelling Techniques For Evolutionary Optimization of Computationally Expensive Problems: Promise and Limitations", Proceeding of the Genetic and Evolutionary Computation Conference, 1999.
15. Y. Jin, M. Olhofer, B. Sendhoff, "A Framework for Evolutionary Optimization with Approximate Fitness Function", IEEE Transactions on Evolutionary Computation, Vol. 6, No. 5, October 2002.
16. H. Ulmer, F. Streichert and A. Zell, "Model-assisted Evolution Strategies", In Y. Jin, editor, Knowledge Incorporation in Evolutionary Computation, pages 333-357. Springer, Berlin, 2004.
17. H. Ulmer, F. Streichert, and A. Zell, "Evolution strategies assisted by Gaussian processes with improved pre-selection criterion", Proceedings of IEEE Congress on Evolutionary Computation, pp. 692-699, 2003.
18. Y. Jin and B. Sendhoff, "Fitness approximation in evolutionary computation: A survey", Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1105-1112, 2002.
19. J.E. Dennis, V. Torczon, "Managing Approximation Models in Optimization and Nonlinear Equations", Prentice Hall, Anglewood Cliffs, NJ, 1983.
20. N.M. Alexandrov, J.E. Dennis, R.M. Lewis, and V. Torczon, "A Trust Region Framework for Managing Use of Approximation Models in Optimization", Journal on Structural Optimization, Vol. 15, No. 1, pp. 16-23, 1998.
21. Y.S. Ong, P.B. Nair, and A.J. Keane, "Evolutionary Optimization of Computationally Expensive Problems via Surrogate Modeling", AIAA Journal, Vol. 41, No. 4, pp 687-696, 2003.
22. Y.S. Ong, P.B. Nair, K.Y. Lum, "Evolutionary Algorithm with Hermite Radial Basis Function Interpolants for Computationally Expensive Adjoint Solvers", Computational Optimization and Applications, conditionally accepted, 2005.
23. J. Morè, "Recent Developments in Algorithms and Software for Trust Region Methods", Mathematical Programming. The State of Art, Bonn 1982, Bachem A., Grotschel, and Korte B., eds., Springer-Verlag, Berlin, 1983, pp. 258-287.
24. V. Vapnik, "Statistical Learning Theory", John Wiley and Sons, NY, 1998.
25. C. Bishop, "Neural Networks for Pattern Recognition", Oxford University Press, 1995.
26. K.C. Giannakoglou, "Design of Optimal Aerodynamic Shapes Using Stochastic Optimization Methods and Computational Intelligence", International Review Journal Progress in Aerospace Sciences, vol. 38, No. 5, pp. 43-76, 2002.
27. H.M. Gutmann, "On the Semi-norm of Radial Basis Function interpolants", Dept. Applied Math. Theor. Phy., Univ. Cambridge, UK., Tech. Rep. DAMTP 2000/NA04, 2000.
28. C.T. Lawrence and A.L. Tits, "A Computationally Efficient Feasible Sequential Quadratic Programming Algorithm", Society for Industrial and Applied Mathematics, Vol. 11, No. 4, pp. 1092-1118, 2001.