A hybrid one-then-two stage algorithm for computationally expensive electromagnetic design optimization

COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

Volumn 26, Issue 2, 2007, Pages 236-246

  Hawe, Glenn ^a   Sykulski, Jan ^b  

^a Vector Fields Ltd   (United Kingdom)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

Optimization techniques

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; FUNCTION EVALUATION; ITERATIVE METHODS; OPTIMIZATION;

ELECTROMAGNETIC DESIGN; KRIGING ALGORITHMS; OPTIMIZATION ALGORITHMS; UTILITY FUNCTIONS;

ELECTROMAGNETS;

EID: 34147200157     PISSN: 03321649     EISSN: None     Source Type: Journal    
DOI: 10.1108/03321640710727601     Document Type: Article

References (16)

1. Gutmann, H.M. (2001), "A radial basis function method for global optimization", Journal of Global Optimization, Vol. 19 No. 3, pp. 201-27.
2. Hawe, G.I. and Sykulski, J.K. (2007), "Considerations of accuracy and uncertainty with Kriging surrogate models in single-objective electromagnetic design optimization", IET Science, Measurement and Technology, in press.
3. Jones, D.R. (2001), "A taxonomy of global optimization methods based on response surfaces", Journal of Global Optimization, Vol. 21, pp. 345-83.
4. Jones, D.R., Schonlau, M. and Welch, W.J. (1998), "Efficient global optimization of expensive black-box functions", Journal of Global Optimization, Vol. 13, pp. 455-92.
5. Kalagnanam, J.R. and Diwekar, U.M. (1997), "An efficient sampling technique for off-line quality control", Technometrics, Vol. 39 No. 3, pp. 308-19.
6. Lebensztajn, L., Marretto, C.A.R., Costa, M.C. and Coulomb, J.-L. (2004), "Kriging: a useful tool for electromagnetic devices optimization", IEEE Transactions on Magnetics, Vol. 40 No. 2, pp. 1196-9.
7. Locateli, M. (1997), "Bayesian algorithms for one-dimensional global optimization", Journal of Global Optimization, Vol. 10, pp. 57-76.
8. Matlab (2004), High-Performance Computation and Visualization Software Reference Guide, The MathWorks Inc., Natick, MA.
9. Nelder, J.A. and Mead, R. (1965), "A simplex method for function minimization", Computer Journal, Vol. 7, pp. 308-13.
10. Santner, T.J., Williams, B. and Notz, W. (2003), The Design and Analysis of Computer Experiments, Springer-Verlag, New York, NY.
11. Sasena, M.J. (2002), "Flexibility and efficency enhancements for constrained global design optimization with Kriging approximations", PhD dissertation, University of Michigan, Ann Arbor, MI.
12. Sasena, M.J., Papalambros, P. and Goovaerts, P. (2002), "Exploration of metamodelling sampling criteria for constrained global optimization", Engineering Optimization, Vol. 34, pp. 263-78.
13. Schonlau, M., Welch, W.J. and Jones, D.R. (1998), "Global versus local search in constrained optimization of computer models", IMS Lecture Notes, Institute of Mathematical Statistics, Beachwood, OH.
14. Sobester, A., Leary, S.J. and Keane, A.J. (2005), "On the design of optimization strategies based on global response surface approximation models", Journal of Global Optimization, Vol. 33, pp. 31-59.
15. Vapnik, V. (2006), Estimation of Dependences Based on Empirical Data, 2nd ed., Springer-Verlag, New York, NY.
16. Dixon, L.C.W. and Szegö, G.P. (1978), "The global optimization problem: an introduction", Towards Global Optimisation 2, North-Holland Publishing Company, Amsterdam.