Searched for: subject:"robust%5C+optimization"
(1 - 20 of 20)
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
Marquez Calvo, O.O. (author), Solomatine, D.P. (author)
This paper considers the problem of robust optimization, and presents the technique called Robust Optimization and Probabilistic Analysis of Robustness (ROPAR). It has been developed for finding robust optimum solutions of a particular class in model-based multi-objective optimization (MOO) problems (i.e. when the objective function is not known...
journal article 2019
document
Eling, R.P.T. (author)
In the competitive automotive market, the performance of turbochargers is constantly being pushed towards their theoretical optimum. One of the key components of the turbocharger is the rotor-bearing system, which determines the friction losses and noise output and furthermore affects the overall turbocharger efficiency, reliability and cost. In...
doctoral thesis 2018
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
Goncalves Dias De Barros, E. (author)
Over the past decades, many technological advances have unlocked new opportunities to boost efficiency in the oil and gas industry (e.g., complex well drilling, injection of advanced chemicals, sophisticated instrumentation). The real engineering challenge is to apply these technologies in the best possible way for each particular case. This...
doctoral thesis 2018
document
Siraj, M.M. (author), van den Hof, P.M.J. (author), Jansen, J.D. (author)
Model-based dynamic optimization of the water-flooding process in oil reservoirs is a computationally complex problem and suffers from high levels of uncertainty. A traditional way of quantifying uncertainty in robust water-flooding optimization is by considering an ensemble of uncertain model realizations. These models are generally not...
conference paper 2017
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
document
Morales-España, G. (author), Davidson, M. (author), Ramírez-Elizondo, L. (author), De Weerdt, M.M. (author)
This document is an online companion for the paper "Robust Unit Commitment with Dispatchable Wind: An LP Reformulation of the Second-stage".
report 2015
document
ur Rehman, S. (author), Langelaar, M. (author)
A novel technique for efficient global robust optimization of problems affected by parametric uncertainties is proposed. The method is especially relevant to problems that are based on expensive computer simulations. The globally robust optimal design is obtained by searching for the best worst-case cost, which involves a nested min-max...
journal article 2015
document
Van der Gun, J.P.T. (author), Pel, A.J. (author), Van Arem, B. (author)
There are many kinds of disasters that can severely impact the transportation system of an urbanized region. Transportation authorities therefore need to develop management strategies to adequately deal with such emergencies. In this paper, we discuss the structure of a simulation model that can be used to assess a candidate strategy. We model...
conference paper 2014
document
Fonseca, R.M. (author), Stordahl, A. (author), Leeuwenburgh, O. (author), Van den Hof, P.M.J. (author), Jansen, J.D. (author)
We consider robust ensemble-based multi-objective optimization using a hierarchical switching algorithm for combined long-term and short term water flooding optimization. We apply a modified formulation of the ensemble gradient which results in improved performance compared to earlier formulations. We also apply multi-dimensional scaling to...
conference paper 2014
document
Hamarat, C. (author), Pruyt, E. (author), Loonen, E.T. (author)
Adaptivity is essential for dynamically complex and uncertain systems. Adaptive policymaking is an approach to design policies that can be adapted over time to how the future unfolds. It is crucial for adaptive policymaking to specify under what conditions and how to adapt the policy. The performance of adaptive policy is critically depended on...
conference paper 2013
document
Ridolfi, G. (author)
The research can be placed in the framework of designing methods for complex systems focused on the conceptual design phase of the systems’ life-cycle. More specifically, the methods presented in the dissertation belong to the category of Operational Research methods. They aim at the creation of design and analysis tools in support of the...
doctoral thesis 2013
document
Hamarat, C. (author), Kwakkel, J.H. (author), Pruyt, E. (author)
The recent flu pandemic in 2009 caused a panic about the possible consequences due to deep uncertainty about an unknown virus. Overstock of vaccines or unnecessary social measures to be taken were all due to uncertainty. However, what should be the necessary actions to take in such deeply uncertain situation where there is no or very little...
conference paper 2012
document
Chaerani, D. (author)
This thesis deals with optimization problems with uncertain data. Uncertainty here means that the data is not known exactly at the time when its solution has to be determined. In many models the uncertainty is ignored and a representative nominal value of the data is used. The uncertainty may be due to measurement or modelling errors or simply...
doctoral thesis 2006
Searched for: subject:"robust%5C+optimization"
(1 - 20 of 20)