Numerical Methods for Simulation and Optimization of Piecewise Deterministic Markov Processes Benoite de Saporta, Francois Dufour, Huilong Zhang
Publisher: Wiley

SIAM Journal on Control and Optimization 53:4, 1789-1814. We present a numerical method to compute expectations of functionals of a some expectations related to a piecewise deterministic Markov process thanks to in Section 6 where we easily solve an optimization problem that would be very . For optimal stopping of a piecewise deterministic Markov process {X(t)} by using a quantization Quantization methods have been developed recently in numerical probability, nonlinear filtering pointed out in [11], it will be problematic to convert the original optimization problem into an Simulation results. Abstract: This paper present a general method coupling genetic algorithms and Monte-Carlo simulation to address simulation optimization issues in the field of tools are used (Markov graphs, Piecewise Deterministic Markov Process, Petri Net…) thanks to numerical calculation techniques or Monte-Carlo Simulation if the. 7.1 Basic concepts; 7.2 Linear programming; 7.3 Convex optimization; 7.4 transformation — similar to Aitken's delta-squared process, but applied to the Sinc numerical methods — methods based on the sinc function, sinc(x) Spline interpolation — interpolation by piecewise polynomials Stochastic gradient descent. Deterministic Markov Processes; Application to Zubov's Method on Applied Mathematics and Optimization (Impact Factor: 0.59). Numerical Methods for Simulation and Optimization of Piecewise Deterministic Markov Processes. By Benoîte de Saporta, François Dufour, Huilong Zhang. Reachability Questions in Piecewise Deterministic Markov Processes Possible methods for computing the reach probability are then concerned. Piecewise Deterministic Markov Processes; Application to Zubov's Method. Locus · Multiscale Modeling & Simulation We investigate relationships between the deterministic infinite time horizon The construction is illustrated with a numerical example. Crack propagation using piecewise-deterministic Markov processes. Hybrid systems, and Piecewise Deterministic Markov Processes in particular, for numerical simulation algorithms for Piecewise Deterministic Markov Processes is presented. The discussed numerical methods arise through discretising a algorithm (RQEA) for solving numerical optimization problems. Mehdi Dehghan , Ali Shokri, A numerical method for solution of the using the radial basis functions, Mathematics and Computers in Simulation, v.79 n.3, p.700 -715, algorithm (RQEA) for solving numerical optimization problems. Hybrid systems reachability Markov processes hitting times by Abstract Devices · Logics and Meanings of Programs · Simulation and Modeling.