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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

This expository paper contains a concise introduction to some significant works concerning the Karush-Kuhn-Tucker condition, a necessary condition for a solution in local optimality in problems with equality and inequality constraints. The…

Optimization and Control · Mathematics 2020-06-08 Zhuoyu Xiao

Most existing work focuses on the generalization of KKT for nonsmooth convex optimization problems, but this paper explores a generalized form of Karush-Kuhn-Tucker (KKT) conditions for real continuous optimization problems.

Optimization and Control · Mathematics 2020-04-09 Stanley Yang

Given a non-convex optimization problem, we study conditions under which every Karush-Kuhn-Tucker (KKT) point is a global optimizer. This property is known as KT-invexity and allows to identify the subset of problems where an interior point…

Optimization and Control · Mathematics 2017-07-07 Ksenia Bestuzheva , Hassan Hijazi

The purpose of this paper is to characterize the weak efficient solutions, the efficient solutions, and the isolated efficient solutions of a given vector optimization problem with finitely many convex objective functions and infinitely…

Optimization and Control · Mathematics 2016-08-11 Miguel A. Goberna , Nader Kanzi

This paper presents a novel approach to solving convex optimization problems by leveraging the fact that, under certain regularity conditions, any set of primal or dual variables satisfying the Karush-Kuhn-Tucker (KKT) conditions is…

Machine Learning · Computer Science 2024-10-22 Shreya Arvind , Rishabh Pomaje , Rajshekhar V Bhat

A neural network-based approach for solving parametric convex optimization problems is presented, where the network estimates the optimal points given a batch of input parameters. The network is trained by penalizing violations of the…

Optimization and Control · Mathematics 2024-09-17 Carmine Delle Femine

We consider a special class of nonconvex semidefinite programming problems and show that every point satisfying the Karush--Kuhn--Tucker (KKT) conditions is globally optimal despite nonconvexity. This property is related to pseudoconvex…

Optimization and Control · Mathematics 2025-06-23 Akatsuki Nishioka , Yoshihiro Kanno

In the last two decades, the sequential optimality conditions, which do not require constraint qualifications and allow improvement on the convergence assumptions of algorithms, had been considered in the literature. It includes the work by…

Optimization and Control · Mathematics 2025-01-27 Ellen H. Fukuda , Kosuke Okabe

In this paper, we are interested in the existence of Pareto solutions to vector polynomial optimization problems over a basic closed semi-algebraic set. By invoking some powerful tools from real semi-algebraic geometry, we first introduce…

Optimization and Control · Mathematics 2022-02-22 Yarui Duan , Liguo Jiao , Pengcheng Wu , Yuying Zhou

We consider choice of the regularization parameter in Tikhonov method if the noise level of the data is unknown. One of the best rules for the heuristic parameter choice is the quasi-optimality criterion where the parameter is chosen as the…

Numerical Analysis · Mathematics 2018-09-10 Toomas Raus , Uno Hämarik

We study a multiobjective variational problem on time scales. For this problem, necessary and sufficient conditions for weak local Pareto optimality are given. We also prove a necessary optimality condition for the isoperimetric problem…

Optimization and Control · Mathematics 2009-09-18 Agnieszka B. Malinowska , Delfim F. M. Torres

This paper studies approximate solutions of a linear fractional vector optimization problem without requiring boundedness of the constraint set. We establish necessary and sufficient conditions for approximating weakly efficient points of…

Optimization and Control · Mathematics 2024-12-12 Nguyen Thi Thu Huong

This paper considers the problem of solving a special quartic-quadratic optimization problem with a single sphere constraint, namely, finding a global and local minimizer of…

Optimization and Control · Mathematics 2019-08-05 Haixiang Zhang , Andre Milzarek , Zaiwen Wen , Wotao Yin

In this work, optimality conditions and classical results from duality theory are derived for continuous-time linear optimization problems with inequality constraints. The optimality conditions are given in the Karush-Kuhn-Tucker form. Weak…

Optimization and Control · Mathematics 2023-05-10 Valeriano Antunes de Oliveira

An essential component of many sophisticated metaheuristics for solving combinatorial optimization problems is some variation of a local search routine that iteratively searches for a better solution within a chosen set of immediate…

Quantum Physics · Physics 2025-02-05 M. Podobrii , V. Kuzmin , V. Voloshinov , M. Veshchezerova , M. R. Perelshtein

This paper deals with Pareto solutions of a nonsmooth fractional interval-valued multiobjective optimization. We first introduce four types of Pareto solutions of the considered problem by considering the lower-upper interval order relation…

Optimization and Control · Mathematics 2022-12-26 Nguyen Huy Hung , Nguyen Van Tuyen

In this paper, we consider multi-objective optimization problems with a sparsity constraint on the vector of variables. For this class of problems, inspired by the homonymous necessary optimality condition for sparse single-objective…

Optimization and Control · Mathematics 2024-03-07 Matteo Lapucci , Pierluigi Mansueto

A class of time-optimal control problems governed by semilinear parabolic equations with mixed pointwise constraints and final point constraints is considered. By introducing the so-called locally optimal solution to time-optimal control…

Optimization and Control · Mathematics 2024-11-13 Huynh Khanh , Bui Trong Kien , Arnd Rösch

In this paper, a robust sequential quadratic programming method for constrained optimization is generalized to problem with an {expectation} objective function {and} deterministic equality and inequality constraints. A stochastic line…

Optimization and Control · Mathematics 2024-10-07 Songqiang Qiu , Vyacheslav Kungurtsev