TY - GEN
T1 - Experience with approximations in the trust-region parallel direct search algorithm
AU - Shontz, S. M.
AU - Howle, V. E.
AU - Hough, P. D.
PY - 2009
Y1 - 2009
N2 - Recent years have seen growth in the number of algorithms designed to solve challenging simulation-based nonlinear optimization problems. One such algorithm is the Trust-Region Parallel Direct Search (TRPDS) method developed by Hough and Meza. In this paper, we take advantage of the theoretical properties of TRPDS to make use of approximation models in order to reduce the computational cost of simulation-based optimization. We describe the extension, which we call mTRPDS, and present the results of a case study for two earth penetrator design problems. In the case study, we conduct computational experiments with an array of approximations within the mTRPDS algorithm and compare the numerical results to the original TRPDS algorithm and a trust-region method implemented using the speculative gradient approach described by Byrd, Schnabel, and Shultz. The results suggest new ways to improve the algorithm.
AB - Recent years have seen growth in the number of algorithms designed to solve challenging simulation-based nonlinear optimization problems. One such algorithm is the Trust-Region Parallel Direct Search (TRPDS) method developed by Hough and Meza. In this paper, we take advantage of the theoretical properties of TRPDS to make use of approximation models in order to reduce the computational cost of simulation-based optimization. We describe the extension, which we call mTRPDS, and present the results of a case study for two earth penetrator design problems. In the case study, we conduct computational experiments with an array of approximations within the mTRPDS algorithm and compare the numerical results to the original TRPDS algorithm and a trust-region method implemented using the speculative gradient approach described by Byrd, Schnabel, and Shultz. The results suggest new ways to improve the algorithm.
KW - Approximation models
KW - Nonlinear programming
KW - Parallel optimization
UR - http://www.scopus.com/inward/record.url?scp=68849098430&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-01970-8_49
DO - 10.1007/978-3-642-01970-8_49
M3 - Conference contribution
AN - SCOPUS:68849098430
SN - 3642019692
SN - 9783642019692
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 501
EP - 510
BT - Computational Science - ICCS 2009 - 9th International Conference, Proceedings
T2 - 9th International Conference on Computational Science, ICCS 2009
Y2 - 25 May 2009 through 27 May 2009
ER -