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In this paper we propose and analyze a method based on the Riccati transformation for solving the evolutionary Hamilton-Jacobi-Bellman equation arising from the stochastic dynamic optimal allocation problem. We show how the fully nonlinear…

Portfolio Management · Quantitative Finance 2013-07-25 Sona Kilianova , Daniel Sevcovic

We present high-order compact schemes for a linear second-order parabolic partial differential equation (PDE) with mixed second-order derivative terms in two spatial dimensions. The schemes are applied to option pricing PDE for a family of…

Computational Finance · Quantitative Finance 2016-11-02 Bertram Düring , Christof Heuer

We study a stochastic optimal control problem with the state constrained to a smooth, compact domain. The control influences both the drift and a possibly degenerate, control-dependent dispersion matrix, leading to a fully nonlinear,…

Optimization and Control · Mathematics 2025-08-08 Anderson O. Calixto , Bernardo Freitas Paulo da Costa , Glauco Valle

An optimal control problem is considered for a stochastic differential equation containing a state-dependent regime switching, with a recursive cost functional. Due to the non-exponential discounting in the cost functional, the problem is…

Optimization and Control · Mathematics 2017-12-29 Hongwei Mei , Jiongmin Yong

This paper considers linear-quadratic control of a non-linear dynamical system subject to arbitrary cost. I show that for this class of stochastic control problems the non-linear Hamilton-Jacobi-Bellman equation can be transformed into a…

General Physics · Physics 2009-11-11 H. J. Kappen

In networked control systems, communication resource constraints often necessitate the use of \emph{sparse} control input vectors. A prototypical problem is how to ensure controllability of a linear dynamical system when only a limited…

Systems and Control · Electrical Eng. & Systems 2025-06-24 Krishna Praveen V. S. Kondapi , Chandrasekhar Sriram , Geethu Joseph , Chandra R. Murthy

This paper introduces a new type of second order stochastic backward Hamilton-Jacobi-Bellman (HJB) equations for optimal stochastic control problems with a currently observable but non-predicable parameter process, in addition to the…

Optimization and Control · Mathematics 2020-03-04 Nikolai Dokuchaev

We study the time-dependent Navier-Stokes equations in the context of stochastic finite element discretizations. Specifically, we assume that the viscosity is a random field given in the form of a generalized polynomial chaos expansion, and…

Numerical Analysis · Mathematics 2026-01-14 Bedřich Sousedík , Randy Price

Stochastic optimization algorithms update models with cheap per-iteration costs sequentially, which makes them amenable for large-scale data analysis. Such algorithms have been widely studied for structured sparse models where the sparsity…

Machine Learning · Computer Science 2019-05-10 Baojian Zhou , Feng Chen , Yiming Ying

We propose and analyse a fully-discrete discontinuous Galerkin time-stepping method for parabolic Hamilton--Jacobi--Bellman equations with Cordes coefficients. The method is consistent and unconditionally stable on rather general…

Numerical Analysis · Mathematics 2017-03-16 Iain Smears , Endre Süli

This paper investigates the convergence properties of the upwind difference scheme for the Hamilton--Jacobi--Bellman (HJB) equation, a central partial differential equation in optimal control theory. First, assuming the existence of a…

Numerical Analysis · Mathematics 2026-02-05 Daisuke Inoue , Yuji Ito , Takahito Kashiwabara , Norikazu Saito , Hiroaki Yoshida

This work introduces a new method to efficiently solve optimization problems constrained by partial differential equations (PDEs) with uncertain coefficients. The method leverages two sources of inexactness that trade accuracy for speed:…

Optimization and Control · Mathematics 2019-05-20 Matthew J. Zahr , Kevin T. Carlberg , Drew P. Kouri

Recent work has established an empirically successful framework for adapting learning rates for stochastic gradient descent (SGD). This effectively removes all needs for tuning, while automatically reducing learning rates over time on…

Machine Learning · Computer Science 2013-03-28 Tom Schaul , Yann LeCun

This paper presents a new method for synthesizing stochastic control Lyapunov functions for a class of nonlinear stochastic control systems. The technique relies on a transformation of the classical nonlinear Hamilton-Jacobi-Bellman partial…

Optimization and Control · Mathematics 2017-09-07 Yoke Peng Leong , Matanya B. Horowitz , Joel W. Burdick

We address the problem of combined stochastic and impulse control for a market maker operating in a limit order book. The problem is formulated as a Hamilton-Jacobi-Bellman quasi-variational inequality (HJBQVI). We propose an implicit…

Mathematical Finance · Quantitative Finance 2025-12-25 Alexey Meteykin

We develop numerical schemes for solving the isothermal compressible and incompressible equations of fluctuating hydrodynamics on a grid with staggered momenta. We develop a second-order accurate spatial discretization of the diffusive,…

We consider a pathwise stochastic optimal control problem and study the associated (not necessarily adapted) Hamilton-Jacobi-Bellman stochastic partial differential equation. We show that the value process is the unique solution of this…

Probability · Mathematics 2023-11-02 Neeraj Bhauryal , Ana Bela Cruzeiro , Carlos Oliveira

This paper addresses the numerical solution of backward stochastic differential equations (BSDEs) arising in stochastic optimal control. Specifically, we investigate two BSDEs: one derived from the Hamilton-Jacobi-Bellman equation and the…

Optimization and Control · Mathematics 2025-03-12 Yuhang Mei , Amirhossein Taghvaei

We present a new formulation for the computation of solutions of a class of Hamilton Jacobi Bellman (HJB) equations on closed smooth surfaces of co-dimension one. For the class of equations considered in this paper, the viscosity solution…

Numerical Analysis · Mathematics 2020-08-06 Lindsay Martin , Richard Tsai

We develop efficient hierarchical preconditioners for optimal control problems governed by partial differential equations with uncertain coefficients. Adopting a discretize-then-optimize framework that integrates finite element…

Optimization and Control · Mathematics 2026-02-24 Zhendong Li , Akwum Onwunta , Bedřich Sousedík
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