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Semiconvex regression for metamodeling-based optimization

Publication ,  Journal Article
Hannah, LA; Powell, WB; Dunson, DB
Published in: SIAM Journal on Optimization
January 1, 2014

Stochastic search involves finding a set of controllable parameters that minimizes an unknown objective function using a set of noisy observations. We consider the case when the unknown function is convex and a metamodel is used as a surrogate objective function. Often he data are non-i.i.d. and include an observable state variable, such as applicant information in a loan rate decision problem. State information is difficult to incorporate into convex models. We propose a new semiconvex regression method that is used to produce a convex metamodel in the presence of a state variable. We show consistency for this method. We demonstrate its effectiveness for metamodeling on a set of synthetic inventory management problems and a large real-life auto loan dataset. © 2014 Society for Industrial and Applied Mathematics.

Duke Scholars

Published In

SIAM Journal on Optimization

DOI

ISSN

1052-6234

Publication Date

January 1, 2014

Volume

24

Issue

2

Start / End Page

573 / 597

Related Subject Headings

  • Operations Research
  • 4901 Applied mathematics
  • 0103 Numerical and Computational Mathematics
  • 0102 Applied Mathematics
 

Citation

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Hannah, L. A., Powell, W. B., & Dunson, D. B. (2014). Semiconvex regression for metamodeling-based optimization. SIAM Journal on Optimization, 24(2), 573–597. https://doi.org/10.1137/130907070
Hannah, L. A., W. B. Powell, and D. B. Dunson. “Semiconvex regression for metamodeling-based optimization.” SIAM Journal on Optimization 24, no. 2 (January 1, 2014): 573–97. https://doi.org/10.1137/130907070.
Hannah LA, Powell WB, Dunson DB. Semiconvex regression for metamodeling-based optimization. SIAM Journal on Optimization. 2014 Jan 1;24(2):573–97.
Hannah, L. A., et al. “Semiconvex regression for metamodeling-based optimization.” SIAM Journal on Optimization, vol. 24, no. 2, Jan. 2014, pp. 573–97. Scopus, doi:10.1137/130907070.
Hannah LA, Powell WB, Dunson DB. Semiconvex regression for metamodeling-based optimization. SIAM Journal on Optimization. 2014 Jan 1;24(2):573–597.

Published In

SIAM Journal on Optimization

DOI

ISSN

1052-6234

Publication Date

January 1, 2014

Volume

24

Issue

2

Start / End Page

573 / 597

Related Subject Headings

  • Operations Research
  • 4901 Applied mathematics
  • 0103 Numerical and Computational Mathematics
  • 0102 Applied Mathematics