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The most important ingredient for solving mixed-integer nonlinear programs (MINLPs) to global epsilon-optimality with spatial branch and bound is a tight, computationally tractable relaxation. Due to both theoretical and practical…

Optimization and Control · Mathematics 2019-12-03 Benjamin Müller , Gonzalo Muñoz , Maxime Gasse , Ambros Gleixner , Andrea Lodi , Felipe Serrano

We consider the problem of learning a linear subspace from data corrupted by outliers. Classical approaches are typically designed for the case in which the subspace dimension is small relative to the ambient dimension. Our approach works…

Computer Vision and Pattern Recognition · Computer Science 2019-11-11 Manolis C. Tsakiris , Rene Vidal

In this study, we introduce an innovative deep learning framework that employs a transformer model to address the challenges of mixed-integer programs, specifically focusing on the Capacitated Lot Sizing Problem (CLSP). Our approach, to our…

Artificial Intelligence · Computer Science 2024-05-27 Joshua F. Cooper , Seung Jin Choi , I. Esra Buyuktahtakin

We consider the disjoint bilinear programming problem in which one of the disjoint subsets has the structure of an acute-angled polytope. An optimality criterion for such a problem is formulated and proved, and based on this, a polynomial…

Optimization and Control · Mathematics 2025-02-13 Dmitrii Lozovanu

Answer Set Programming (ASP) is a truly-declarative programming paradigm proposed in the area of non-monotonic reasoning and logic programming, that has been recently employed in many applications. The development of efficient ASP systems…

Artificial Intelligence · Computer Science 2020-02-19 Marco Maratea , Luca Pulina , Francesco Ricca

A double pivot algorithm that combines features of two recently published papers by these authors is proposed. The proposed algorithm is implemented in MATLAB. The MATLAB code is tested, along with a MATLAB implementation of Dantzig's…

Optimization and Control · Mathematics 2025-07-08 Yaguang Yang , Fabio Vitor

We show how to efficiently compute the derivative (when it exists) of the solution map of log-log convex programs (LLCPs). These are nonconvex, nonsmooth optimization problems with positive variables that become convex when the variables,…

Optimization and Control · Mathematics 2020-06-02 Akshay Agrawal , Stephen Boyd

With this note we bring again into attention a vector dual problem neglected by the contributions who have recently announced the successful healing of the trouble encountered by the classical duals to the classical linear vector…

Optimization and Control · Mathematics 2019-11-13 Radu Ioan Bot , Sorin-Mihai Grad , Gert Wanka

Several well known large scale linear programming decomposition methodologies exist. Benders Decomposition, which covers the case where some small subset of variables link the otherwise separable subproblems. Dantzig-Wolfe decomposition and…

Optimization and Control · Mathematics 2020-03-04 Bruce A. Cox

A class of non-convex optimization problems with DC objective function is studied, where DC stands for being representable as the difference $f=g-h$ of two convex functions $g$ and $h$. In particular, we deal with the special case where one…

Optimization and Control · Mathematics 2017-04-06 Andreas Löhne , Andrea Wagner

We consider a multi-objective risk-averse two-stage stochastic programming problem with a multivariate convex risk measure. We suggest a convex vector optimization formulation with set-valued constraints and propose an extended version of…

Optimization and Control · Mathematics 2017-11-20 Çağın Ararat , Özlem Çavuş , Ali İrfan Mahmutoğulları

The latent variable proximal point (LVPP) algorithm is a framework for solving infinite-dimensional variational problems with pointwise inequality constraints. The algorithm is a saddle point reformulation of the Bregman proximal point…

Optimization and Control · Mathematics 2025-07-01 Jørgen S. Dokken , Patrick E. Farrell , Brendan Keith , Ioannis P. A. Papadopoulos , Thomas M. Surowiec

A Geometric programming (GP) is a type of mathematical problem characterized by objective and constraint functions that have a special form. Many methods have been developed to solve large scale engineering design GP problems. In this paper…

Data Structures and Algorithms · Computer Science 2009-12-10 Dr. A. K. Ojha , K. K. Biswal

We consider parametric linear programming problems with multiple objective functions depending linearly on some parameter. Both parametric (single-objective) linear programming and (non-parametric) multi-objective linear programming are…

Optimization and Control · Mathematics 2026-02-16 Kezang Yuden , Levin Nemesch , Stefan Ruzika

This paper presents fast first-order methods for solving linear programs (LPs) approximately. We adapt online linear programming algorithms to offline LPs and obtain algorithms that avoid any matrix multiplication. We also introduce a…

Optimization and Control · Mathematics 2024-11-07 Wenzhi Gao , Dongdong Ge , Chunlin Sun , Yinyu Ye

Despite the success of branch-and-cut methods for solving mixed integer bilevel linear optimization problems (MIBLPs) in practice, there are still gaps in both the theory and practice surrounding these methods. In the first part of this…

Optimization and Control · Mathematics 2025-10-06 Sahar Tahernejad , Ted K. Ralphs

Several algorithms are available in the literature for finding the entire set of Pareto-optimal solutions in MultiObjective Linear Programming (MOLP). However, it has not been proposed so far an interior point algorithm that finds all…

Optimization and Control · Mathematics 2011-12-30 Víctor Blanco , Justo Puerto , Safae El-Haj Ben-Ali

We present a simple and efficient MATLAB implementation of the linear virtual element method for the three dimensional Poisson equation. The purpose of this software is primarily educational, to demonstrate how the key components of the…

Numerical Analysis · Mathematics 2022-02-21 Yue Yu

In this paper, we describe a comprehensive algorithmic framework for solving mixed integer bilevel linear optimization problems (MIBLPs) using a generalized branch-and-cut approach. The framework presented merges features from existing…

Optimization and Control · Mathematics 2021-04-20 Sahar Tahernejad , Ted K. Ralphs , Scott T. DeNegre

Bilevel programs are optimization problems where some variables are solutions to optimization problems themselves, and they arise in a variety of control applications, including: control of vehicle traffic networks, inverse reinforcement…

Optimization and Control · Mathematics 2017-09-27 Aurélien Ouattara , Anil Aswani
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