Preconditioning the augmented Lagrangian method for instationary mean field games with diffusion
Andreev, Roman (2017), Preconditioning the augmented Lagrangian method for instationary mean field games with diffusion, SIAM Journal on Scientific Computing;1064-8275, 39, 6, p. A2763–A2783. 10.1137/16M1072346
TypeArticle accepté pour publication ou publié
Journal nameSIAM Journal on Scientific Computing;1064-8275
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Laboratoire Jacques-Louis Lions [LJLL]
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Abstract (EN)We discuss the application of the augmented Lagrangian method to the convex optimization problem of instationary variational mean field games with diffusion. The problem is first discretized with space-time tensor product piecewise polynomial bases. This leads to a sequence of linear problems posed on the space-time cylinder that are second order in the temporal variable and fourth order in the spatial variable. To solve these large linear problems with the preconditioned conjugate gradients method we propose a preconditioner that is based on a temporal transformation coupled with a spatial multigrid. This preconditioner is thus based on standard components and is particularly suitable for parallel computation. It is conditionally parameter-robust in the sense that the condition number of the preconditioned system is low for sufficiently fine temporal discretizations. Numerical examples illustrate the method.
Subjects / KeywordsB-splines; multigrid; preconditioning; discretization; space-time; augmented Lagrangian; ALG2; ADMM; mean field games
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