Results 161 to 170 of about 9,123 (200)

A new domain decomposition method for an HJB equation

Journal of Computational and Applied Mathematics, 2003
This note is concerned with a second-order Hamilton-Jacobi-Bellman (HJB) equation. First, the authors explain that this kind of problems can be regarded as a quasivaritional inequality problem. Further, they proceed by a domain decomposition to establish the solution.
Shuzi Zhou
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A power penalty method for discrete HJB equations

Optimization Letters, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kai  Zhang, X Q Yang
exaly   +4 more sources

On Computation of Optimal Switching HJB Equation

Proceedings of the 45th IEEE Conference on Decision and Control, 2006
This paper proposes an algorithm to compute the optimal switching cost from the dynamic programming Hamilton-Jacobi-Bellman (HJB) equations. For the optimal switching control problem, the HJB equation is a System of Quasi-Variational Inequalities (SQVIs) coupled by a nonlinear operator. By exploring the fundamental limit on the number of switches could
Huan Zhang, Matthew R. James
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Consistency of Generalized Finite Difference Schemes for the Stochastic HJB Equation [PDF]

SIAM Journal on Numerical Analysis, 2003
Summary: We analyze a class of numerical schemes for solving the HJB equation for stochastic control problems, which enters the framework of Markov chain approximations and generalizes the usual finite difference method. The latter is known to be monotonic, and hence valid, only if the scaled covariance matrix is dominant diagonal.
J Frédéric Bonnans, Hasnaa Zidani
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A new iterative method for discrete HJB equations

Numerische Mathematik, 2008
The goal of this paper is to propose a successive relaxation iterative algorithm for discrete Hamilton-Jacobi-Bellman equation: \((1) \max_{1\leq j\leq K} \{A^JU-F^J\}=0\) where \(A^j \in \mathbb R^{n \times n}, F^j \in \mathbb R^n, j=1,2,\dots K\). Equation (1) is a system of nonsmooth nonlinear equations. A successive iterative scheme, similar to the
Shuzi Zhou, Zhanyong Zou
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Modifications of the PCPT method for HJB equations

AIP Conference Proceedings, 2016
In this paper we will revisit the modification of the piecewise constant policy timestepping (PCPT) method for solving Hamilton-Jacobi-Bellman (HJB) equations. This modification is called piecewise predicted policy timestepping (PPPT) method and if properly used, it may be significantly faster.
I. Kossaczký, M. Ehrhardt, M. Günther
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Dynamic Programming and HJB Equations

1999
In this chapter we turn to study another powerful approach to solving optimal control problems, namely, the method of dynamic programming. Dynamic programming, originated by R. Bellman in the early 1950s, is a mathematical technique for making a sequence of interrelated decisions, which can be applied to many optimization problems (including optimal ...
Jiongmin Yong, Xun Yu Zhou
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Regularity Properties for General HJB Equations: A Backward Stochastic Differential Equation Method

SIAM Journal on Control and Optimization, 2012
In this work we investigate regularity properties of a large class of Hamilton-Jacobi- Bellman (HJB) equations with or without obstacles, which can be stochastically interpreted in the form of a stochastic control system in which nonlinear cost functional is defined with the help of a backward stochastic differential equation (BSDE) or a reflected BSDE.
Rainer Buckdahn, Jianhui Huang
exaly   +3 more sources

Pathwise Stochastic Control Problems and Stochastic HJB Equations

SIAM Journal on Control and Optimization, 2007
In this paper we study a class of pathwise stochastic control problems in which the optimality is allowed to depend on the paths of exogenous noise (or information). Such a phenomenon can be illustrated by considering a particular investor who wants to take advantage of certain extra information but in a completely legal manner.
Rainer Buckdahn, Jin Ma
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HJB Equations Through Backward Stochastic Differential Equations

2017
This last chapter of the book completes the picture of the main methods used to study second-order HJB equations in Hilbert spaces and related optimal control problems by presenting a survey of results that can be achieved with the techniques of Backward SDEs in infinite dimension.
Fuhrman, M, Tessitore, G.
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