Exploration of metamodeling sampling criteria for constrained global optimization

Engineering Optimization

Volumn 34, Issue 3, 2002, Pages 263-278

  Sasena, Michael J ^a   Papalambros, Panos ^a   Goovaerts, Pierre ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

Author keywords

Approximation; Computer simulation; Global optimization; Kriging

Indexed keywords

COMPUTER SIMULATION; CONSTRAINT THEORY; ITERATIVE METHODS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; PROBABILITY DISTRIBUTIONS;

CONSTRAINED GLOBAL OPTIMIZATION; EFFICIENT GLOBAL OPTIMIZATION; METAMODELLING;

GLOBAL OPTIMIZATION;

EID: 0036588666     PISSN: 0305215X     EISSN: None     Source Type: Journal    
DOI: 10.1080/03052150211751     Document Type: Article

References (14)

1. Assanis, D., Delagrammatikas, G., Fellini, R., Filipi, Z., Liedtke, J., Michelena, N., Papalambros, P., Reyes, D., Rosenbaum, D., Sales, A. and Sasena, M. (1999). An optimization approach to hybrid electric propulsion system design. Journal of Mechanics of Structures and Machines, Automotive Research Center Special Edition Issue, Haug, E. J. (Ed.), 27(4), 393-421.
2. Audet, C., Dennis, J. E. Jr., Moore, D. W., Booker, A. and Frank, P. D. (2000). A surrogate-model-based method for constrained optimization. Proceedings of the 8th AIAA/NASA/USAF/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Long Beach, CA, Paper No. AIAA-2000-4891.
3. Dixon, L. C. W. and Szegö, G. P. (1978). The global optimisation problem: An introduction Towards Global Optimisation 2. North-Holland Publishing Company.
4. Fellini, R., Papalambros, P. and Weber, T. (2000). Application of a product platform design process to automotive powertrains. Proceedings of the 8th AIAA/NASA/USAF/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Long Beach, CA, Paper No. AIAA-2000-4849.
5. Fellini, R., Michelena, N., Papalambros, P. and Sasena, M. (1999). Optimal design of automotive hybrid powertrain systems. IEEE EcoDesign '99 Conference, Tokyo, Japan.
6. Gomez, S. and Levy, A. (1982). The tunneling method for solving the constrained global optimization problem with several non-connected feasible regions. In: Dold, A. and Eckmann, B. (Eds.), Lecture Notes in Mathematics 909, Springer-Verlag. pp. 34-47.
7. Goovaerts, P. (1997). Geostatistics for Natural Evaluation. Oxford University Press, New York.
8. Jones, D. R., Perttunen, C. D. and Stuckman, B. E. (1993). Lipschitzian optimization without the lipschitz constant. Journal of Optimization Theory and Application, 79, 157-181.
9. Jones, D. R., Schonlau, M. and Welch, W. J. (1998). Efficient global optimization of expensive black-box functions. Journal of Global Optimization, 13(4), 455-492.
10. National Renewable Energy Laboratory, Department of Energy. [Web Site] URL: http://www.ctts.nrel.gov/analysis/ [Retrieved on 2001, July 4].
11. Sasena, M. J., Papalambros, P. Y. and Goovaerts, P. (2001). The use of surrogate modeling algorithms to exploit disparities in function computation time within simulation-based optimization. The Fourth World Congress of Structural and Multidisciplinary Optimization, Dalian, China.
12. Sasena, M. J., Papalambros, P. Y. and Goovaerts, P. (2000). Metamodeling sampling criteria in a global optimization framework. Proceedings of the 8th AIAA/NASA/USAF/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Long Beach, CA, Paper No. AIAA-2000-4921.
13. Schonlau, M, (1997). Computer experiments and global optimization. Doctoral Dissertation, Department of Statistics, University of Waterloo.
14. Watson, A. G. and Barnes, R. J. (1995). Infill sampling criteria to locate extremes. Mathematical Geology, 27(5), 589-608.