Title
Robust Optimization of PDEs with Random Coefficients Using a Multilevel Monte Carlo Method
Abstract
This paper addresses optimization problems constrained by partial differential equations with uncertain coefficients. In particular, the robust control problem and the average control problem are considered for a tracking type cost functional with an additional penalty on the variance of the state. The expressions for the gradient and Hessian corresponding to either problem contain expected value operators. Due to the large number of uncertainties considered in our model, we suggest evaluating these expectations using a multilevel Monte Carlo (MLMC) method. Under mild assumptions, it is shown that this results in the gradient and Hessian corresponding to the MLMC estimator of the original cost functional. Furthermore, we show that the use of certain correlated samples yields a reduction in the total number of samples required. Two optimization methods are investigated: the nonlinear conjugate gradient method and the Newton method. For both, a specific algorithm is provided that dynamically decides which and how many samples should be taken in each iteration. The cost of the optimization up to some specified tolerance tau is shown to be proportional to the cost of a gradient evaluation with requested root mean square error tau. The algorithms are tested on a model elliptic diffusion problem with lognormal diffusion coefficient. An additional nonlinear term is also considered.
Year
DOI
Venue
2017
10.1137/17M1155892
SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION
Keywords
Field
DocType
robust optimization,stochastic PDEs,multilevel Monte Carlo,optimal control,uncertainty,gradient,Hessian
Mathematical optimization,Monte Carlo method,Robust optimization,Hybrid Monte Carlo,Hessian matrix,Quasi-Monte Carlo method,Nonlinear conjugate gradient method,Monte Carlo integration,Optimization problem,Mathematics
Journal
Volume
Issue
ISSN
7
1
2166-2525
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Andreas Van Barel100.34
Stefan Vandewalle250162.63