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There are many important practical optimization problems whose feasible regions are not known to be nonempty or not, and optimizers of the objective function with the least constraint violation prefer to be found. A natural way for dealing…

Optimization and Control · Mathematics 2021-11-12 Yu-Hong Dai , Liwei Zhang

We analyze a fractional mean field game of controls system, showing existence of solutions when the order of the fractional Laplacian is $s\in(\frac{1}{2},1)$. Here the running cost depends on the distribution $\mu$ of not only the states…

Analysis of PDEs · Mathematics 2025-09-08 P. Jameson Graber , Elizabeth Matter , Jesus Ruiz Bolanos

In this paper we consider a non-monotone (mixed) variational inequality model with (nonlinear) convex conic constraints. Through developing an equivalent Lagrangian function-like primal-dual saddle-point system for the VI model in question,…

Optimization and Control · Mathematics 2023-06-05 Lei Zhao , Daoli Zhu , Shuzhong Zhang

This paper is mainly concerned with the solutions to both forward and backward mean-field stochastic partial differential equation and the corresponding optimal control problem for mean-field stochastic partial differential equation. We…

Optimization and Control · Mathematics 2016-10-11 Maoning Tang , Qingxin Meng

We contribute improvements to a Lagrangian dual solution approach applied to large-scale optimization problems whose objective functions are convex, continuously differentiable and possibly nonlinear, while the non-relaxed constraint set is…

Optimization and Control · Mathematics 2019-08-09 Brian Dandurand , Natashia Boland , Jeffrey Christiansen , Andrew Eberhard , Fabricio Oliveira

We propose an augmented Lagrangian-type algorithm for the solution of generalized Nash equilibrium problems (GNEPs). Specifically, we discuss the convergence properties with regard to both feasibility and optimality of limit points. This is…

Optimization and Control · Mathematics 2018-07-13 Christian Kanzow , Daniel Steck

This paper proposes a partially inexact alternating direction method of multipliers for computing approximate solution of a linearly constrained convex optimization problem. This method allows its first subproblem to be solved inexactly…

Optimization and Control · Mathematics 2018-05-21 Vando A. Adona , Max L. N. Goncalves , Jefferson G. Melo

In this work, we study a class of mean-field linear quadratic Gaussian (LQG) problems. Under suitable conditions, explicit solutions of the distribution-dependent optimal control problems are obtained. Riccati systems are derived by…

Probability · Mathematics 2020-08-28 Yun Li , Qingshuo Song , Fuke Wu , George Yin

Variational methods have been used to study stochastic control for long, see Bensoussan (1982) and Bensoussan-Lions (1978) for the early works. More precisely, variational approaches apply to the study of Bellman equation as a parabolic…

Optimization and Control · Mathematics 2025-12-01 Alain Bensoussan , Ziyu Huang , Sheung Chi Phillip Yam

In this paper we study homogenization of a class of control problems in a stationary and ergodic random environment. This problem has been mostly studied in the calculus of variations setting in connection to the homogenization of the…

Analysis of PDEs · Mathematics 2018-06-21 Alexander Van-Brunt

In this paper, we consider nonlinear optimization problems with nonlinear equality constraints and bound constraints on the variables. For the solution of such problems, many augmented Lagrangian methods have been defined in the literature.…

Optimization and Control · Mathematics 2022-01-12 Andrea Cristofari , Gianni Di Pillo , Giampaolo Liuzzi , Stefano Lucidi

We consider a mean-field control problem in which admissible controls are required to be adapted to the common noise filtration. The main objective is to show how the mean-field control problem can be approximates by time consistent…

Optimization and Control · Mathematics 2025-09-19 Bruno Bouchard , Xiaolu Tan

We study the convergence problem of mean-field control theory in the presence of state constraints and non-degenerate idiosyncratic noise. Our main result is the convergence of the value functions associated to stochastic control problems…

Optimization and Control · Mathematics 2023-06-02 Samuel Daudin

This paper is concerned with optimal control problems for systems governed by mean-field stochastic differential equation, in which the control enters both the drift and the diffusion coefficient. We prove that the relaxed state process,…

Optimization and Control · Mathematics 2017-02-03 Khaled Bahlali , Meriem Mezerdi , Brahim Mezerdi

This paper studies optimal control and stabilization problems for continuous-time mean-field systems with input delay, which are the fundamental development of control and stabilization problems for mean-field systems. There are two main…

Optimization and Control · Mathematics 2020-10-19 Xiao Ma , Qingyuan Qi , Xun Li , Huanshui Zhang

In this paper, we propose a penalty dual-primal augmented lagrangian method for solving convex minimization problems under linear equality or inequality constraints. The proposed method combines a novel penalty technique with updates the…

Optimization and Control · Mathematics 2023-05-09 Jie Liu , Xiaoqing Ou , Jiawei Chen

Local convergence analysis of the augmented Lagrangian method (ALM) is established for a large class of composite optimization problems with nonunique Lagrange multipliers under a second-order sufficient condition. We present a new…

Optimization and Control · Mathematics 2023-10-23 Nguyen T. V. Hang , Ebrahim Sarabi

In this paper, we propose a variational Lagrangian scheme for a modified phase-field model, which can compute the equilibrium states for the original Allen-Cahn type model. Our discretization is based on a prescribed energy-dissipation law…

Numerical Analysis · Mathematics 2020-08-24 Chun Liu , Yiwei Wang

A gauge independent method of obtaining the reduced space of constrained dynamical systems is discussed in a purely lagrangian formalism. Implications of gauge fixing are also considered.

High Energy Physics - Theory · Physics 2007-05-23 R. Banerjee

Mean-field games (MFGs) are models for large populations of competing rational agents that seek to optimize a suitable functional. In the case of congestion, this functional takes into account the difficulty of moving in high-density areas.…

Analysis of PDEs · Mathematics 2017-10-05 David Evangelista , Rita Ferreira , Diogo A. Gomes , Levon Nurbekyan , Vardan Voskanyan