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This study investigates a stochastic production planning problem with a running cost composed of quadratic production costs and inventory-dependent costs. The objective is to minimize the expected cost until production stops when inventory…

Optimization and Control · Mathematics 2025-05-20 Dragos-Patru Covei

We study a novel general class of multidimensional type-I backward stochastic Volterra integral equations. Toward this goal, we introduce an infinite dimensional system of standard backward SDEs and establish its well-posedness, and we show…

Probability · Mathematics 2020-08-05 Camilo Hernández , Dylan Possamaï

In this paper, we first establish the dynamic programming principle for stochastic optimal control problems defined on compact Riemannian manifolds without boundary. Subsequently, we derive the associated Hamilton-Jacobi-Bellman (HJB)…

Optimization and Control · Mathematics 2025-07-03 Dingqian Gao , Qi Lü

This paper studies an optimal stochastic impulse control problem in a finite horizon with a decision lag, by which we mean that after an impulse is made, a fixed number units of time has to be elapsed before the next impulse is allowed to…

Optimization and Control · Mathematics 2021-02-09 Chang Li , Jiongmin Yong

The present paper considers a stochastic optimal control problem, in which the cost function is defined through a backward stochastic differential equation with infinite horizon driven by G-Brownian motion. Then we study the regularities of…

Probability · Mathematics 2017-06-13 Mingshang Hu , Falei Wang

In this paper, a stochastic optimal control problem is investigated in which the system is governed by a stochastic functional differential equation. In the framework of functional It\^o calculus, we build the dynamic programming principle…

Optimization and Control · Mathematics 2013-01-03 Shaolin Ji , Shuzhen Yang

We study the stochastic control-stopping problem when the data are of polynomial growth. The approach is based on backward stochastic dierential equations (BSDEs for short). The problem turns into the study of a specic reected BSDE with a…

Optimization and Control · Mathematics 2020-05-15 Brahim Asri , Said Hamadène , Khalid Oufdil

Linear-quadratic optimal control problem for systems governed by forward-backward stochastic differential equations has been extensively studied over the past three decades. Recent research has revealed that for forward-backward control…

Optimization and Control · Mathematics 2025-04-22 Qi Lü , Bowen Ma , Hanxiao Wang

We propose a new probabilistic numerical scheme for fully nonlinear equation of Hamilton-Jacobi-Bellman (HJB) type associated to stochastic control problem, which is based on the Feynman-Kac representation in [12] by means of control…

Probability · Mathematics 2019-06-28 Idris Kharroubi , Nicolas Langrené , Huyên Pham

In the present work we employ, for the first time, backward stochastic differential equations (BSDEs) to study the optimal control of semi-Markov processes on finite horizon, with general state and action spaces. More precisely, we prove…

Optimization and Control · Mathematics 2015-05-27 Elena Bandini , Fulvia Confortola

We study a class of optimal control problems with state constraints where the state equation is a differential equation with delays. This class includes some problems arising in economics, in particular the so-called models with time to…

Optimization and Control · Mathematics 2009-07-09 Salvatore Federico , Ben Goldys , Fausto Gozzi

In this paper, we study the delayed stochastic recursive optimal control problem with a non-Lipschitz generator, in which both the dynamics of the control system and the recursive cost functional depend on the past path segment of the state…

Optimization and Control · Mathematics 2023-12-27 Jiaqiang Wen , Zhen Wu , Qi Zhang

In this paper, we study a stochastic recursive optimal control problem in which the value functional is defined by the solution of a backward stochastic differential equation (BSDE) under $\tilde{G}$-expectation. Under standard assumptions,…

Optimization and Control · Mathematics 2021-06-08 Mingshang Hu , Shaolin Ji , Xiaojuan Li

The dynamic programming approach is one of the most powerful ones in optimal control. However, when dealing with optimal control problems of stochastic Volterra integral equations (SVIEs) with completely monotone kernels, deep mathematical…

Optimization and Control · Mathematics 2026-02-20 Gabriele Bolli , Filippo de Feo

In this paper, we study an optimal control problem of linear backward stochastic differential equation (BSDE) with quadratic cost functional under partial information. This problem is solved completely and explicitly by using a stochastic…

Optimization and Control · Mathematics 2020-12-16 Guangchen Wang , Wencan Wang , Zhiguo Yan

Infinite horizon backward stochastic Volterra integral equations (BSVIEs for short) are investigated. We prove the existence and uniqueness of the adapted M-solution in a weighted $L^2$-space. Furthermore, we extend some important known…

Probability · Mathematics 2021-10-28 Yushi Hamaguchi

We formulate and analyze a new method for solving optimal control problems for systems governed by Volterra integral equations. Our method utilizes discretization of the original Volterra controlled system and a novel type of dynamic…

Optimization and Control · Mathematics 2007-05-23 S. A. Belbas

We consider the optimal control problem of stochastic evolution equations in a Hilbert space under a recursive utility, which is described as the solution of a backward stochastic differential equation (BSDE). A very general maximum…

Optimization and Control · Mathematics 2024-02-06 Guomin Liu , Shanjian Tang

In this paper, we study backward doubly stochastic recursive optimal control problem where the cost function is described by the solution of a backward doubly stochastic differential equation. We give the dynamical programming principle for…

Probability · Mathematics 2020-08-13 Yunhong Li , Anis. Matoussi , Lifeng Wei , Zhen Wu

This work addresses stochastic optimal control problems where the unknown state evolves in continuous time while partial, noisy, and possibly controllable measurements are only available in discrete time. We develop a framework for…

Optimization and Control · Mathematics 2025-08-19 Christian Bayer , Boualem Djehiche , Eliza Rezvanova , Raul Fidel Tempone