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Binary optimization is a central problem in mathematical optimization and its applications are abundant. To solve this problem, we propose a new class of continuous optimization techniques which is based on Mathematical Programming with…

Optimization and Control · Mathematics 2017-12-07 Ganzhao Yuan , Bernard Ghanem

This paper presents the first study of the complexity of the optimization problem for integer linear-exponential programs which extend classical integer linear programs with the exponential function $x \mapsto 2^x$ and the remainder…

Logic in Computer Science · Computer Science 2025-10-17 S Hitarth , Alessio Mansutti , Guruprerana Shabadi

We study the existence of polynomial kernels for the problem of deciding feasibility of integer linear programs (ILPs), and for finding good solutions for covering and packing ILPs. Our main results are as follows: First, we show that the…

Computational Complexity · Computer Science 2013-02-18 Stefan Kratsch

A great variety of fundamental optimization and counting problems arising in computer science, mathematics and physics can be reduced to one of the following computational tasks involving polynomials and set systems: given an $m$-variate…

Data Structures and Algorithms · Computer Science 2016-11-15 Damian Straszak , Nisheeth K. Vishnoi

Extended formulations are an important tool in polyhedral combinatorics. Many combinatorial optimization problems require an exponential number of inequalities when modeled as a linear program in the natural space of variables. However, by…

Optimization and Control · Mathematics 2024-06-07 Christoph Buchheim

This paper considers an optimization problem for a dynamical system whose evolution depends on a collection of binary decision variables. We develop scalable approximation algorithms with provable suboptimality bounds to provide…

Optimization and Control · Mathematics 2016-10-31 Insoon Yang , Samuel A. Burden , Ram Rajagopal , S. Shankar Sastry , Claire J. Tomlin

Linear programming (LP) relaxations are widely employed in exact solution methods for multilinear programs (MLP). One example is the family of Recursive McCormick Linearization (RML) strategies, where bilinear products are substituted for…

Optimization and Control · Mathematics 2022-07-20 Arvind U Raghunathan , Carlos Cardonha , David Bergman , Carlos J Nohra

Packing and covering semidefinite programs (SDPs) appear in natural relaxations of many combinatorial optimization problems as well as a number of other applications. Recently, several techniques were proposed, that utilize the particular…

Data Structures and Algorithms · Computer Science 2019-02-19 Khaled Elbassioni , Kazuhisa Makino

A number of theoretical and computational problems for matrix polynomials are solved by passing to linearizations. Therefore a perturbation theory results for linearizations need to be related back to matrix polynomials. In this paper we…

Numerical Analysis · Mathematics 2020-08-06 Andrii Dmytryshyn

This paper studies the polynomial optimization problem whose feasible set is a union of several basic closed semialgebraic sets. We propose a unified hierarchy of Moment-SOS relaxations to solve it globally. Under some assumptions, we prove…

Optimization and Control · Mathematics 2024-05-21 Jiawang Nie , Linghao Zhang

In this paper, we consider a bilevel polynomial optimization problem where the objective and the constraint functions of both the upper and the lower level problems are polynomials. We present methods for finding its global minimizers and…

Optimization and Control · Mathematics 2016-01-14 V. Jeyakumar , J. B. Lasserre , G. Li , T. S. Pham

We study relaxations for linear programs with complementarity constraints, especially instances whose complementary pairs of variables are not independent. Our formulation is based on identifying vertex covers of the conflict graph of the…

Optimization and Control · Mathematics 2022-08-03 Alberto Del Pia , Jeff Linderoth , Haoran Zhu

This paper is our third step towards developing a theory of testing monomials in multivariate polynomials and concentrates on two problems: (1) How to compute the coefficients of multilinear monomials; and (2) how to find a maximum…

Computational Complexity · Computer Science 2015-05-19 Zhixiang Chen , Bin Fu

In this paper we develop a very special substitution method for solving a general linear programming problem (LPP). Of course the substitution is a kind of elimination of variable but this method must not be confused with the so-called…

Optimization and Control · Mathematics 2026-05-07 Laurent Truffet

In this paper, we develop new discrete relaxations for nonlinear expressions in factorable programming. We utilize specialized convexification results as well as composite relaxations to develop mixed-integer programming (MIP) relaxations.…

Optimization and Control · Mathematics 2024-06-18 Taotao He , Mohit Tawarmalani

The work in this paper is to initiate a theory of testing monomials in multivariate polynomials. The central question is to ask whether a polynomial represented by certain economically compact structure has a multilinear monomial in its…

Computational Complexity · Computer Science 2010-07-19 Zhixiang Chen , Bin Fu

We consider discrete bilevel optimization problems where the follower solves an integer program with a fixed number of variables. Using recent results in parametric integer programming, we present polynomial time algorithms for pure and…

Optimization and Control · Mathematics 2017-01-03 Matthias Köppe , Maurice Queyranne , Christopher Thomas Ryan

A polynomial algorithm is obtained for the NP-complete linear ordering problem.

Computational Complexity · Computer Science 2007-05-23 Givi Bolotashvili

In this paper, we will show that the width of simplices defined by systems of linear inequalities can be computed in polynomial time if some minors of their constraint matrices are bounded. Additionally, we present some…

Optimization and Control · Mathematics 2022-11-30 D. V. Gribanov , A. Y. Chirkov

We consider the problem of black-box function optimization over the boolean hypercube. Despite the vast literature on black-box function optimization over continuous domains, not much attention has been paid to learning models for…