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In this study, we examine Fritz John (FJ) and Karush-Kuhn-Tucker (KKT) type optimality conditions for a class of nonsmooth and nonconvex optimization problems with inequality constraints, where the objective and constraint functions all are…

Optimization and Control · Mathematics 2025-09-03 Refail Kasimbeyli , Jian-Wen Peng , Jen-Chih Yao

The Kantorovich function $(x^TAx)(x^T A^{-1} x)$, where $A$ is a positive definite matrix, is not convex in general. From matrix/convex analysis point of view, it is interesting to address the question: When is this function convex? In this…

Optimization and Control · Mathematics 2010-08-05 Yun-Bin Zhao

We establish a geometric condition guaranteeing exact copositive relaxation for the nonconvex quadratic optimization problem under two quadratic and several linear constraints, and present sufficient conditions for global optimality in…

Optimization and Control · Mathematics 2017-10-04 I. M. Bomze , V. Jeyakumar , G. Li

In this paper, we derive a new linear convergence rate for the gradient method with fixed step lengths for non-convex smooth optimization problems satisfying the Polyak-Lojasiewicz (PL) inequality. We establish that the PL inequality is a…

Optimization and Control · Mathematics 2022-04-05 Hadi Abbaszadehpeivasti , Etienne de Klerk , Moslem Zamani

We consider optimization problems in Lebesgue spaces with pointwise box constraints and finitely many additional linear constraints. We prove that the existence of a Slater point which lies strictly between the pointwise bounds and which…

Optimization and Control · Mathematics 2024-03-05 Gerd Wachsmuth

To every nearly convex optimization problem, that is a minimization problem with a nearly convex objective function and a nearly convex constraint set, we associate a uniquely defined convex optimization problem with a lower semicontinuous…

Optimization and Control · Mathematics 2026-02-11 Nguyen Nang Thieu , Nguyen Dong Yen

We study the singular stochastic optimal control problem with model uncertainty, where the necessary conditions determined by the corresponding maximum principle are trivial. Robust integral form and pointwise second order necessary…

Optimization and Control · Mathematics 2025-12-09 Guangdong Jing

This paper presents a canonical duality theory for solving a general nonconvex constrained optimization problem within a unified framework to cover Lagrange multiplier method and KKT theory. It is proved that if both target function and…

Optimization and Control · Mathematics 2013-10-09 Vittorio Latorre , David Y. Gao

Study about theory and algorithms for constrained optimization usually assumes that the feasible region of the optimization problem is nonempty. However, there are many important practical optimization problems whose feasible regions are…

Optimization and Control · Mathematics 2020-10-07 Yu-Hong Dai , Liwei Zhang

In this paper, we derive first and second-order optimality conditions of KKT type for locally optimal solutions to a class of multiobjective optimal control problems with endpoint constraint and mixed pointwise constraints. We give some…

Optimization and Control · Mathematics 2024-11-18 Samir Adly , Bui Trong Kien

The paper proposes and justifies a new algorithm of the proximal Newton type to solve a broad class of nonsmooth composite convex optimization problems without strong convexity assumptions. Based on advanced notions and techniques of…

Optimization and Control · Mathematics 2022-03-02 Boris S. Mordukhovich , Xiaoming Yuan , Shangzhi Zeng , Jin Zhang

In this paper, we study the perturbation analysis of a class of composite optimization problems, which is a very convenient and unified framework for developing both theoretical and algorithmic issues of constrained optimization problems.…

Optimization and Control · Mathematics 2026-03-23 Peipei Tang , Chengjing Wang

This paper deals with approximate solutions of an optimization problem with interval-valued objective function. Four types of approximate solution concepts of the problem are proposed by considering the partial ordering $LU$ on the set of…

Optimization and Control · Mathematics 2020-12-07 Nguyen Van Tuyen

This paper is concerned with the derivation of necessary conditions for the optimal shape of a design problem governed by a non-smooth PDE. The main particularity thereof is the lack of differentiability of the nonlinearity in the state…

Optimization and Control · Mathematics 2024-09-24 Livia Betz

We introduce a new form of Lagrangian and propose a simple first-order algorithm for nonconvex optimization with nonlinear equality constraints. We show the algorithm generates bounded dual iterates, and establish the convergence to KKT…

Optimization and Control · Mathematics 2023-05-10 Jong Gwang Kim

In this paper, we consider the convergence of an abstract inexact nonconvex and nonsmooth algorithm. We promise a pseudo sufficient descent condition and a pseudo relative error condition, which are both related to an auxiliary sequence,…

Optimization and Control · Mathematics 2018-11-29 Tao Sun , Hao Jiang , Lizhi Cheng , Wei Zhu

This paper is devoted to studying the robust isolated calmness of the Karush-Kuhn-Tucker (KKT) solution mapping for a large class of interesting conic programming problems (including most commonly known ones arising from applications) at a…

Optimization and Control · Mathematics 2016-10-04 Chao Ding , Defeng Sun , Liwei Zhang

This paper pursues a two-fold goal. Firstly, we aim to derive novel second-order characterizations of important robust stability properties of perturbed Karush-Kuhn-Tucker systems for a broadclass of constrained optimization problems…

Optimization and Control · Mathematics 2020-04-15 Ashkan Mohammadi , Boris Mordukhovich , Ebrahim Sarabi

Although the Karush-Kuhn-Tucker conditions suggest a connection between a conic optimization problem and a complementarity problem, it is difficult to find an accessible explicit form of this relationship in the literature. This note will…

Optimization and Control · Mathematics 2016-07-19 S. Z. Németh , Guohan Zhang

Performance indicators are essential tools for assessing the convergence behavior of multi-objective optimization algorithms, particularly when the true Pareto front is unknown or difficult to approximate. Classical reference-based metrics…

Optimization and Control · Mathematics 2026-03-05 Thiago Santos , Sebastiao Xavier
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