Metamodelling and search using space exploration and unimodal region elimination for design optimization

References

• Barton , R. R. Simulation Metamodels . Proceedings of the 30th Conference on Winter simulation conference . December 13–16 , Washington, D.C. pp. 1167 – 176 . Washington, D.C : IEEE .
   Google Scholar
• Booker , A. J. , Dennis , J. E. , Frank , P. D. , Serafini , D. B. , Torczon , V. and Trosset , M. W. 1999 . A rigorous framework for optimization of expensive functions by surrogates . Structural Optimization , 17 : 1 – 13 .
   Web of Science ®Google Scholar
• Box , G. E.P. and Draper , N. R. 1987 . Empirical model-building and response surfaces , Edited by: Box , G. E.P. and Draper , N. R. New York : John Wiley & Sons, Inc .
   Google Scholar
• Cressie , N. 1988 . Spatial prediction and ordinary Kriging . Mathematical Geology , 20 ( 4 ) : 405 – 421 .
   Google Scholar
• Fang , K.-T. , Lin , D. K.J. , Winker , P. and Zhang , Y. 2000 . Uniform design: Theory and application . Technometrics , 42 ( 3 ) : 237 – 248 .
   Web of Science ®Google Scholar
• Forrester , A. J. and Kean , A. J. 2009 . Recent advances in surrogate-based optimization . Progress in Aerospace Sciences , 45 : 50 – 79 .
   Web of Science ®Google Scholar
• Gill , P. E. , Murray , E. and Wright , M. H. 1981 . Practical optimization , Edited by: Gill , P. E. , Murray , E. and Wright , M. H. New York : Academic Press .
   Google Scholar
• Giunta , A. A. and Watson , L. T. 1998 . A comparison of approximation modeling techniques: Polynomial versus interpolating models . Paper AIAA–98–4758 ,
   Google Scholar
• Hedayat , A. S. , Sloane , N. J.A. and Stuftken , J. 1999 . Orthogonal arrays, theory and applications , Edited by: Hedayat , A. S. , Sloane , N. J.A. and Stuftken , J. New York : Springer .
   Google Scholar
• Helton , J. C. 2005 . Illustration of sampling-based methods for uncertainty and sensitivity analysis . Journal of Risk Analysis , 22 ( 3 ) : 591 – 622 .
   Google Scholar
• Jin , R. , Chen , W. and Sudjianto , A. On sequential sampling for global metamodeling in engineering design . ASME 2002 design engineering technical conferences and computers and information in engineering conference . 29 September–2 October , Montreal, Canada. New York : ASME . DETC 2002/DAC-34092
   Google Scholar
• Jin , R. , Chen , W. and Simpson , T. 2000 . Comparative studies of metamodeling techniques under multiple modeling criteria . Paper AIAA–2000–4801 ,
   Google Scholar
• Jin , R. , Du , X. and Chen , W. 2001 . The use of metamodeling techniques for optimization under uncertainty . Structural and Multidisciplinary Optimization , 23 ( 1 ) : 1 – 13 .
   Web of Science ®Google Scholar
• 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 .
   Web of Science ®Google Scholar
• Kalagnanam , J. R. and Diwekar , U. M. 1997 . An efficient sampling technique for off-line quality control . Technometrics , 39 ( 3 ) : 308 – 319 .
   Web of Science ®Google Scholar
• Martin , F. T.S. and Gonzales , A. P. 2003 . Global optimization in path synthesis based on design space reduction . Mechanics and Machine Theory , 38 : 579 – 594 .
   Web of Science ®Google Scholar
• Martin , J. D. and Simpson , T. W. 2005 . Use of Kriging models to approximate deterministic computer models . AIAA Journal , 43 ( 4 ) : 853 – 863 .
   Web of Science ®Google Scholar
• Mckay , M. D. , Bechman , R. J. and Conver , W. J. 1979 . A comparison of three methods for selecting values of input variables in the analysis techniques for computer codes . Technometrics , 21 ( 2 ) : 239 – 245 .
   Web of Science ®Google Scholar
• Meckesheimer , M. , Barton , R. R. , Simpson , T. W. and Booker , A. J. 2002 . Computationally inexpensive metamodeling assessment strategies . AIAA Journal , 40 ( 10 ) : 2053 – 2060 .
   Web of Science ®Google Scholar
• Melo , V. V.D. , Delbem , A. C.B. , Junior , D. L.P. and Federson , F. M. Improving global numerical optimization using a search-space reduction algorithm . GECCO’07 . July 7–11 , London, England. pp. 1195 – 1202 . New York : ACM Press .
   Google Scholar
• Montgomery , D. C. 2001 . Design and analysis of experiments , 5 , New York : John Wiley & Sons Inc .
   Google Scholar
• Sacks , J. , Schiller , S. B. and Welch , W. J. 1989 . Design for computer experiments . Technometrics , 31 ( 1 ) : 41 – 47 .
   Web of Science ®Google Scholar
• Sasena , M. J. , Papalambros , P. and Goovaerts , P. Global optimization of problems with disconnected feasible region via surrogate modeling . Proceedings of the 9th AIAA/ISSMO symposium on multidisciplinary analysis and optimization . September 4–6 , Atlanta, GA. New York : AIAA . Paper AIAA 2002-5573
   Google Scholar
• Shan , S. and Wang , G. 2004 . Space exploration and global optimization for computationally intensive design problems: A rough set based approach . Structural Multidisciplinary Optimization , 28 : 427 – 441 .
   Web of Science ®Google Scholar
• Simpson , T. W. , Mauery , T. M. , Korte , J. J. and Mistree , F. 2001 . Kriging models for global approximation in simulation based multidisciplinary design optimization . American Institute of Aeronautics and Astronautics , 39 ( 12 ) : 2233 – 2241 .
   Google Scholar
• Simpson , T. W. , Pepliniski , J. D. , Koch , P. N. and Allen , J. K. 2001 . Metamodeling for computer-based engineering design: Survey and recommendations . Engineering with Computers , 17 : 129 – 150 .
   Web of Science ®Google Scholar
• Sobieszczanski-Sobieski , J. and Haftka , R. T. 1997 . Multidisciplinary aerospace design optimization: Survey of recent developments . Structural Optimization , 14 : 1 – 23 .
   Web of Science ®Google Scholar
• Tang , B. 1993 . Orthogonal array based Latin Hypercubes . Journal of American Statistical Association , 88 ( 424 ) : 1392 – 1397 .
   Web of Science ®Google Scholar
• Thomas , W. 2009 . Global optimization algorithms, theory and applications , 2 Edited by: Thomas , W. Available at: http://www.it-weise.de/projects/book.pdf
   Google Scholar
• Wang , G. , Dong , Z. and Aitchison , P. 2001 . Adaptive response surface method. A global optimization scheme for approximation-based design problems . Journal of Mechanical Engineering , 33 : 707 – 733 .
   Google Scholar
• Wang , G. and Simpson , T. W. 2004 . Fuzzy clustering based hierarchical metamodeling for space reduction and design optimization . Engineering Optimization , 36 ( 3 ) : 313 – 335 .
   Web of Science ®Google Scholar
• Wang , L. , Beeson , D. , Akkaram , S. and Wiggs , G. Gaussian process metamodels for efficient probabilistic design in complex engineering design spaces . ASME/DETC international design engineering technical conferences and computers and information in engineering conference . September 24–28 , Long Beach, CA. New York : ASME Press, DETC2005-85406 .
   Google Scholar
• Wang , L. , Shan , S. and Wang , G. 2004 . Mode-pursuing sampling method for global optimization on expensive black-box functions . Engineering Optimization , 36 ( 4 ) : 419 – 438 .
   Web of Science ®Google Scholar
• Younis , A. , Xu , R. and Dong , Z. 2009 . Approximated unimodal region elimination based global optimization method for engineering design . International Journal of Product Development , 9 ( 1/2/3 ) : 164 – 187 .
   Google Scholar
• Zhuge , Q. , Xue , C. , Shao , Z. , Liu , M. , Qui , M. and Sha , E. H.M. 2006 . Design optimization and space minimization considering timing and code size via real timing and unfolding . Microprocessors and Microsystems , 30 : 173 – 183 .
   Web of Science ®Google Scholar