Displaying similar documents to “Implementation of optimal Galerkin and Collocation approximations of PDEs with Random Coefficients⋆⋆⋆”

Temporal convergence of a locally implicit discontinuous Galerkin method for Maxwell’s equations

Ludovic Moya (2012)

ESAIM: Mathematical Modelling and Numerical Analysis

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In this paper we study the temporal convergence of a locally implicit discontinuous Galerkin method for the time-domain Maxwell’s equations modeling electromagnetic waves propagation. Particularly, we wonder whether the method retains its second-order ordinary differential equation (ODE) convergence under stable simultaneous space-time grid refinement towards the true partial differential equation (PDE) solution. This is not clear due to the component splitting which can introduce order...

A survey on combinatorial optimization in dynamic environments

Nicolas Boria, Vangelis T. Paschos (2011)

RAIRO - Operations Research

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This survey presents major results and issues related to the study of NPO problems in dynamic environments, that is, in settings where instances are allowed to undergo some modifications over time. In particular, the survey focuses on two complementary frameworks. The first one is the reoptimization framework, where an instance that is already solved undergoes some local perturbation. The goal is then to make use of the information provided by the initial solution to compute a new solution....

A survey on combinatorial optimization in dynamic environments

Nicolas Boria, Vangelis T. Paschos (2011)

RAIRO - Operations Research

Similarity:

This survey presents major results and issues related to the study of NPO problems in dynamic environments, that is, in settings where instances are allowed to undergo some modifications over time. In particular, the survey focuses on two complementary frameworks. The first one is the reoptimization framework, where an instance that is already solved undergoes some local perturbation. The goal is then to make use of the information provided by the initial solution to compute a new solution....

Numerical algorithms for backward stochastic differential equations with 1-d brownian motion: Convergence and simulations

Shige Peng, Mingyu Xu (2011)

ESAIM: Mathematical Modelling and Numerical Analysis

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In this paper we study different algorithms for backward stochastic differential equations (BSDE in short) basing on random walk framework for 1-dimensional Brownian motion. Implicit and explicit schemes for both BSDE and reflected BSDE are introduced. Then we prove the convergence of different algorithms and present simulation results for different types of BSDEs.