We propose a new non-conforming localized model reduction paradigm for efficient solution of large scale or multiscale PDE constrained optimization problems. The new conceptual approach goes beyond the classical offline/online splitting of traditional projection based model order reduction approaches for the underlying state equation, such as the reduced basis method. Instead of first construct...

This paper proposes a novel surrogate-model-based multiobjective evolutionary algorithm called Differential Evolution for Multiobjective Optimization Based on Gaussian Process Models (GP-DEMO). The algorithm is based on the newly defined relations for comparing solutions under uncertainty. These relations minimize the possibility of wrongly performed comparisons of solutions due to inaccurate s...

We propose a hybrid algorithm for solving global optimization problems that is based on the coupling of the Simultaneous Perturbation Stochastic Approximation (SPSA) and Newton-Krylov Interior-Point (NKIP) methods via a surrogate model. There exist verified algorithms for finding approximate global solutions, but our technique will further guarantee that such solutions satisfy physical bounds o...

For the design and optimization of multistage assembly processes, a computationally cheap mathematical model that links design parameters with the final product dimensional quality is highly desirable. We propose a systematic approach to building a surrogate model of simulations of multistage assembly processes. At the heart of this approach is a multiple-input-multiple-output surrogate modelin...

Evolutionary optimization is often applied to problems, where simulations or experiments used as the fitness function are expensive to run. In such cases, surrogate models are used to reduce the number of fitness evaluations. Some of the problems also require a fixed size batch of solutions to be evaluated at a time. Traditional methods of selecting individuals for true evaluation to improve th...

WENZHEN HUANG1,∗, TIRAWAT PHOOMBOPLAB2,3 and DARIUSZ CEGLAREK2,3 1Department of Mechanical Engineering, University of Massachusetts, Dartmouth, MA 02747, USA E-mail: [email protected] 2Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA 3International Digital Laboratory, WMG, University of Warwick, Coventry CV4 7AL, UK E-mail: {T.Phoomboplab...

A property of nonlinear oscillators—mutual dependence between their instantaneous amplitude and frequency—is tested in the yearly and monthly records of the sunspot numbers using the histogramadjusted isospectral surrogate data and the Barnes model as the autoregressive moving average surrogates. The instantaneous amplitudes and frequencies are obtained by means of the analytic signal approach ...

Jonathan Blackman, Scott E. Field, 3 Mark A. Scheel, Chad R. Galley, Christian D. Ott, 4 Michael Boyle, Lawrence E. Kidder, Harald P. Pfeiffer, and Béla Szilágyi 6 Theoretical Astrophysics 350-17, California Institute of Technology, Pasadena, CA 91125, USA Mathematics Department, University of Massachusetts Dartmouth, Dartmouth, MA 02747, USA Cornell Center for Astrophysics and Planetary Scienc...

For instance nutritional data are often subject to severe measurement error, and an adequate adjustment of the estimators is indispensable to avoid deceptive conclusions. This paper discusses and extends the method of regression calibration to correct for measurement error in Cox regression. Special attention is paid to the modelling of quadratic predictors, the role of heteroscedastic measurem...

Jonathan Blackman, Scott E. Field, Mark A. Scheel, Chad R. Galley, Daniel A. Hemberger, Patricia Schmidt, and Rory Smith Theoretical Astrophysics 350-17, California Institute of Technology, Pasadena, California 91125, USA Cornell Center for Astrophysics and Planetary Science, Cornell University, Ithaca, New York 14853, USA Mathematics Department, University of Massachusetts Dartmouth, Dartmouth...