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This paper is concerned with a Stackelberg game of backward stochastic differential equations (BSDEs), where the coefficients of the backward system and the cost functionals are deterministic, and the control domain is convex. Necessary and…

Optimization and Control · Mathematics 2019-04-18 Yueyang Zheng , Jingtao Shi

Optimal control of heterogeneous mean-field stochastic differential equations with common noise has not been addressed in the literature. In this work, we initiate the study of such models. We formulate the problem within a linear-quadratic…

Optimization and Control · Mathematics 2025-11-25 Filippo de Feo , Samy Mekkaoui

We propose a simple and original approach for solving linear-quadratic mean-field stochastic control problems. We study both finite-horizon and infinite-horizon problems, and allow notably some coefficients to be stochastic. Our method is…

Probability · Mathematics 2017-11-28 Matteo Basei , Huyên Pham

In this paper, we study a class of stochastic time-inconsistent linear-quadratic (LQ) control problems with control input constraints. These problems are investigated within the more general framework associated with random coefficients.…

Optimization and Control · Mathematics 2017-03-29 Ying Hu , Jianhui Huang , Xun Li

This paper focuses on the discrete-time backward stochastic linear quadratic (BSLQ) optimal control problem with nonhomogeneous system terms and cost function cross terms. The terminal constraint of such systems distinguishes it from…

Optimization and Control · Mathematics 2026-04-14 Hu Ligui , Meng Qingxin , Tang Maoning

We study linear-quadratic stochastic optimal control problems with bilinear state dependence for which the underlying stochastic differential equation (SDE) consists of slow and fast degrees of freedom. We show that, in the same way in…

Dynamical Systems · Mathematics 2018-03-21 Omar Kebiri , Lara Neureither , Carsten Hartmann

This article studies convex duality in stochastic optimization over finite discrete-time. The first part of the paper gives general conditions that yield explicit expressions for the dual objective in many applications in operations…

Optimization and Control · Mathematics 2015-04-28 Sara Biagini , Teemu Pennanen , Ari-Pekka Perkkiö

This paper studies duality and optimality conditions for general convex stochastic optimization problems. The main result gives sufficient conditions for the absence of a duality gap and the existence of dual solutions in a locally convex…

Optimization and Control · Mathematics 2022-06-01 Teemu Pennanen , Ari-Pekka Perkkiö

In this paper, we present an equivalent convex optimization formulation for discrete-time stochastic linear systems subject to linear chance constraints, alongside a tight convex relaxation for quadratic chance constraints. By lifting the…

Systems and Control · Electrical Eng. & Systems 2026-03-23 Tanmay Dokania , Yashwanth Kumar Nakka

This paper formulates and studies a stochastic maximum principle for forward-backward stochastic Volterra integral equations (FBSVIEs in short), while the control area is assumed to be convex. Then a linear quadratic (LQ in short) problem…

Probability · Mathematics 2010-04-14 Tianxiao Wang , Yufeng Shi

This paper is concerned with a general linear quadratic (LQ) control problem of mean-field backward stochastic differential equation (BSDE). Here, the weighting matrices in the cost functional are allowed to be indefinite. Necessary and…

Optimization and Control · Mathematics 2024-12-31 Wencan Wang , Huanjun Zhang

This paper studies a continuous-time market {under stochastic environment} where an agent, having specified an investment horizon and a target terminal mean return, seeks to minimize the variance of the return with multiple stocks and a…

Portfolio Management · Quantitative Finance 2013-02-28 Wan-Kai Pang , Yuan-Hua Ni , Xun Li , Ka-Fai Cedric Yiu

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

In this paper, we consider optimal control of stochastic differential equations subject to an expected path constraint. The stochastic maximum principle is given for a general optimal stochastic control in terms of constrained FBSDEs. In…

Optimization and Control · Mathematics 2022-08-16 Ying Hu , Shanjian Tang , Zuo Quan Xu

This paper is devoted to an optimal control problem of fully coupled forward-backward stochastic differential equations driven by sub-diffusion, whose solutions are not Markov processes. The stochastic maximum principle is obtained, where…

Optimization and Control · Mathematics 2025-03-11 Chenhui Hao , Jingtao Shi , Shuaiqi Zhang

Throughout this paper, we focused our aim on the problem of optimal control under a risk-sensitive performance functional, where the system is given by a fully coupled forward-backward stochastic differential equation with jump. The risk…

Optimization and Control · Mathematics 2019-03-07 Rania Khallout , Adel Chala

This paper develops a comprehensive framework for optimal control of systems governed by fractional backward stochastic evolution equations (FBSEEs) in Hilbert spaces. We first establish a stochastic maximum principle (SMP) as a necessary…

Optimization and Control · Mathematics 2026-01-06 Javad A. Asadzade , Nazim I. Mahmudov

This paper extends the domination-monotonicity conditions, which guarantee the well-posedness of extended mean-filed forward-backward stochastic differential equations (extended MF-FBSDEs), from the previously studied linear framework to a…

Optimization and Control · Mathematics 2026-05-12 Hao Wu

We analyze a class of multidimensional linear-quadratic stochastic control problems with random coefficients, motivated by multi-asset optimal trade execution. The problems feature non-diffusive controlled state dynamics and a terminal…

Optimization and Control · Mathematics 2026-01-08 Julia Ackermann , Thomas Kruse , Petr Petrov , Alexandre Popier

In this paper, we discuss the ambiguous chance constrained based portfolio optimization problems, in which the perturbations associated with the input parameters are stochastic in nature, but their distributions are not known precisely. We…

Optimization and Control · Mathematics 2023-11-09 Pulak Swain , Akshay Kumar Ojha