Searched for: subject:"robust%5C%2Boptimization"
(1 - 8 of 8)
document
Jesus de Moraes, R. (author), Fonseca, Rahul Mark (author), Helici, Mircea A. (author), Heemink, A.W. (author), Jansen, J.D. (author)
We present an efficient workflow that combines multiscale (MS) forward simulation and stochastic gradient computation - MS-StoSAG - for the optimization of well controls applied to waterflooding under geological uncertainty. A two-stage iterative Multiscale Finite Volume (i-MSFV), a mass conservative reservoir simulation strategy, is employed as...
journal article 2019
document
Shaéezadeh-Abadeh, Soroosh (author), Kuhn, Daniel (author), Mohajerin Esfahani, P. (author)
The goal of regression and classification methods in supervised learning is to minimize the empirical risk, that is, the expectation of some loss function quantifying the prediction error under the empirical distribution. When facing scarce training data, overfitting is typically mitigated by adding regularization terms to the objective that...
journal article 2019
document
Morales-Espana, G. (author), Lorca, Álvaro (author), de Weerdt, M.M. (author)
The increasing penetration of uncertain generation such as wind and solar in power systems imposes new challenges to the unit commitment (UC) problem, one of the most critical tasks in power systems operations. The two most common approaches to address these challenges — stochastic and robust optimization — have drawbacks that restrict their...
journal article 2018
document
Rehman, S.U. (author), Langelaar, M. (author)
A novel adaptive sampling scheme for efficient global robust optimization of constrained problems is proposed. The method addresses expensive to simulate black-box constrained problems affected by uncertainties for which only the bounds are known, while the probability distribution is not available. An iterative strategy for global robust...
journal article 2017
document
Rehman, S.U. (author), Langelaar, M. (author)
Fabrication variations can have a detrimental effect on the performance of optical filters based on ring resonators. However, by using robust optimization these effects can be minimized and device yield can be significantly improved. This paper presents an efficient robust optimization technique for designing manufacturable optical filters based...
journal article 2016
document
Fonseca, R.M. (author), Chen, B (author), Jansen, J.D. (author), Reynolds, Albert C. (author)
We consider a technique to estimate an approximate gradient using an ensemble of randomly chosen control vectors, known as Ensemble Optimization (EnOpt) in the oil and gas reservoir simulation community. In particular, we address how to obtain accurate approximate gradients when the underlying numerical mod- els contain uncertain parameters...
journal article 2016
document
Perko, Z. (author), van der Voort, S.R. (author), Van De Water, Steven (author), Hartman, C.M.H. (author), Hoogeman, M.S. (author), Lathouwers, D. (author)
The highly conformal planned dose distribution achievable in intensity modulated proton therapy (IMPT) can severely be compromised by uncertainties in patient setup and proton range. While several robust optimization approaches have been presented to address this issue, appropriate methods to accurately estimate the robustness of treatment...
journal article 2016
document
Fonseca, R.M. (author)
In this dissertation we have investigated theoretical and numerical aspects of the Ensemble Optimization (EnOpt) technique for model based production optimization. We have proposed a modified gradient formulation for robust optimization which we show to be theoretically more robust than the earlier existing formulation. Through a series of...
doctoral thesis 2015
Searched for: subject:"robust%5C%2Boptimization"
(1 - 8 of 8)