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The paper is concerned with an optimal control problem governed by the equations of elasto plasticity with linear kinematic hardening and the inertia term at small strain. The objective is to optimize the displacement field and plastic…

Optimization and Control · Mathematics 2023-06-22 Stephan Walther

This paper investigates a time-inconsistent portfolio selection problem in the incomplete mar ket model, integrating expected utility maximization with risk control. The objective functional balances the expected utility and variance on log…

Portfolio Management · Quantitative Finance 2025-12-02 Yue Cao , Zongxia Liang , Sheng Wang , Xiang Yu

We study a stochastic differential game between two players, controlling a forward stochastic Volterra integral equation (FSVIE). Each player has to optimize his own performance functional which includes a backward stochastic differential…

Probability · Mathematics 2023-03-07 Giulia Di Nunno , Michele Giordano

This work presents the multiharmonic analysis and derivation of functional type a posteriori estimates of a distributed eddy current optimal control problem and its state equation in a time-periodic setting. The existence and uniqueness of…

Optimization and Control · Mathematics 2023-08-10 Monika Wolfmayr

We propose a variational formulation of an inverse problem in continuous-time stochastic control, aimed at identifying control costs consistent with a given distribution over trajectories. The formulation is based on minimizing the…

Optimization and Control · Mathematics 2026-03-19 Yumiharu Nakano

In the context of risk measures, the capital allocation problem is widely studied in the literature where different approaches have been developed, also in connection with cooperative game theory and systemic risk. Although static capital…

Probability · Mathematics 2023-05-17 Emanuela Rosazza Gianin , Marco Zullino

In this paper, we generalize to Gaussian Volterra processes the existence and uniqueness of solutions for a class of non linear backward stochastic differential equations (BSDE) and we establish the relation between the non linear BSDE and…

Probability · Mathematics 2020-05-15 Habiba Knani

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

In this work, we study a boundary control problem for the evolutionary Navier-Stokes equations, under mixed boundary conditions, in two dimensions. The cost functional here considered is of quadratic type, depending on both state and…

Optimization and Control · Mathematics 2024-10-02 Telma Guerra , Irene Marín-Gayte , Jorge Tiago

This article presents a new method for computing guaranteed convex and concave relaxations of nonlinear stochastic optimal control problems with final-time expected-value cost functions. This method is motivated by similar methods for…

Optimization and Control · Mathematics 2017-11-27 Yuanxun Shao , Dillard Robertson , Joseph Kirk Scott

In this paper, we study the stochastic Volterra integral equation driven by $G$-Brownian motion ($G$-SVIE). The existence, uniqueness and two types of continuity of the solution to $G$-SVIE are obtained. Moreover, combining a new…

Probability · Mathematics 2025-05-01 Bingru Zhao , Renxing Li , Mingshang Hu

In this paper, the stochastic verification theorems for stochastic control problems of reflected forward-backward stochastic differential equations are studied. We carry out the work within the frameworks of classical and viscosity…

Optimization and Control · Mathematics 2023-06-07 Lu Liu , Xinlei Hu , Qingmeng Wei

We propose a method for open-loop stochastic optimal control of LTI systems based on Taylor approximations of quantile functions. This approach enables efficient computation of quantile functions that arise in chance constrained…

Optimization and Control · Mathematics 2022-09-12 Shawn Priore , Christopher Petersen , Meeko Oishi

In this work we adapt a prediction-correction algorithm for continuous time-varying convex optimization problems to solve dynamic programs arising from Model Predictive Control. In particular, the prediction step tracks the evolution of the…

Systems and Control · Electrical Eng. & Systems 2019-11-25 Santiago Paternain , Manfred Morari , Alejandro Ribeiro

Inverse problems involving partial differential equations (PDEs) are widely used in science and engineering. Although such problems are generally ill-posed, different regularisation approaches have been developed to ameliorate this problem.…

Applications · Statistics 2022-03-23 Jan Povala , Ieva Kazlauskaite , Eky Febrianto , Fehmi Cirak , Mark Girolami

We present a novel method for solving a class of time-inconsistent optimal stopping problems by reducing them to a family of standard stochastic optimal control problems. In particular, we convert an optimal stopping problem with a…

Optimization and Control · Mathematics 2016-11-15 Christopher W. Miller

We present a unified framework for learning continuous control policies using backpropagation. It supports stochastic control by treating stochasticity in the Bellman equation as a deterministic function of exogenous noise. The product is a…

Machine Learning · Computer Science 2015-11-02 Nicolas Heess , Greg Wayne , David Silver , Timothy Lillicrap , Yuval Tassa , Tom Erez

In this paper, we formulate a general time-inconsistent stochastic linear--quadratic (LQ) control problem. The time-inconsistency arises from the presence of a quadratic term of the expected state as well as a state-dependent term in the…

Optimization and Control · Mathematics 2011-11-04 Ying Hu , Hanqing Jin , Xun Yu Zhou

We study a new class of ergodic backward stochastic differential equations (EBSDEs for short) which is linked with semi-linear Neumann type boundary value problems related to ergodic phenomenas. The particularity of these problems is that…

Probability · Mathematics 2010-02-11 Adrien Richou

Sample-based Bayesian inference provides a route to uncertainty quantification in the geosciences, and inverse problems in general, though is very computationally demanding in the naive form that requires simulating an accurate computer…

Computation · Statistics 2019-04-12 Tiangang Cui , Colin Fox , Michael J O'Sullivan
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