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Convexification is a core technique in global polynomial optimization. Currently, there are two main approaches competing in theory and practice: the approach of nonlinear programming and the approach based on positivity certificates from…

Optimization and Control · Mathematics 2021-09-29 Gennadiy Averkov , Benjamin Peters , Sebastian Sager

Binary polynomial optimization is equivalent to the problem of minimizing a linear function over the intersection of the multilinear set with a polyhedron. Many families of valid inequalities for the multilinear set are available in the…

Optimization and Control · Mathematics 2022-09-13 Rui Chen , Sanjeeb Dash , Oktay Gunluk

Solving difficult mixed-integer nonlinear programs via spatial branch-and-bound requires effective convex outer-approximations of nonconvex sets. In this framework, complex problem formulations are decomposed into simpler library functions,…

Optimization and Control · Mathematics 2025-12-17 Lillian Makhoul , Emily Speakman

Motivated by previous efforts toward mathematically analyzing the treatment of monomials in spatial branch-and-bound, we study the convex hull of the graph of a simple monomial on a nonnegative box domain in arbitrary dimension, where at…

Optimization and Control · Mathematics 2026-05-05 Jon Lee , Daphne Skipper , Emily Speakman

Speakman and Lee (2017) gave a formula for the volume of the convex hull of the graph of a trilinear monomial, $y=x_1x_2x_3$, over a box in the nonnegative orthant, in terms of the upper and lower bounds on the variables. This was done in…

Optimization and Control · Mathematics 2019-10-08 Emily Speakman , Gennadiy Averkov

In Speakman and Lee (2017), we analytically developed the idea of using volume as a measure for comparing relaxations in the context of spatial branch-and-bound. Specifically, for trilinear monomials, we analytically compared the three…

Optimization and Control · Mathematics 2018-10-18 Emily Speakman , Jon Lee

This paper considers the approximation of a monomial $x^n$ over the interval $[-1,1]$ by a lower-degree polynomial. This polynomial approximation can be easily computed analytically and is obtained by truncating the analytical Chebyshev…

Numerical Analysis · Mathematics 2021-01-19 Arvind K. Saibaba

We present a novel, general, and unifying point of view on sparse approaches to polynomial optimization. Solving polynomial optimization problems to global optimality is a ubiquitous challenge in many areas of science and engineering.…

Optimization and Control · Mathematics 2024-03-07 Gennadiy Averkov , Benjamin Peters , Sebastian Sager

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

McCormick envelopes are a standard tool for deriving convex relaxations of optimization problems that involve polynomial terms. Such McCormick relaxations provide lower bounds, for example, in branch-and-bound procedures for mixed-integer…

Optimization and Control · Mathematics 2026-01-06 Sven Leyffer , Paul Manns

We describe strong convex valid inequalities for conic quadratic mixed 0-1 optimization. These inequalities can be utilized for solving numerous practical nonlinear discrete optimization problems from value-at-risk minimization to queueing…

Optimization and Control · Mathematics 2018-08-28 Alper Atamturk , Andres Gomez

The aim of this paper is to implement some new techniques, based on conjugate duality in convex optimization, for proving the existence of global error bounds for convex inequality systems. We deal first of all with systems described via…

Optimization and Control · Mathematics 2010-07-13 Radu Ioan Bot , Ernö Robert Csetnek

It is well-known that the convex and concave envelope of a multilinear polynomial over a box are polyhedral functions. Exponential-sized extended and projected formulations for these envelopes are also known. We consider the convexification…

Optimization and Control · Mathematics 2021-06-14 Yibo Xu , Warren Adams , Akshay Gupte

Error bound analysis, which estimates the distance of a point to the solution set of an optimization problem using the optimality residual, is a powerful tool for the analysis of first-order optimization algorithms. In this paper, we use…

Optimization and Control · Mathematics 2020-07-01 Jiawei Zhang , Zhiquan Luo

Recently, motivated by the rapid increase of the data size in various applications, Monemizadeh [APPROX'23] and Driemel, Monemizadeh, Oh, Staals, and Woodruff [SoCG'25] studied geometric problems in the setting where the only access to the…

Computational Geometry · Computer Science 2026-03-24 T. Schibler , J. Xue , J. Zhu

It is well-known that the McCormick relaxation for the bilinear constraint $z=xy$ gives the convex hull over the box domains for $x$ and $y$. In network applications where the domain of bilinear variables is described by a network polytope,…

Optimization and Control · Mathematics 2024-03-27 Erfan Khademnia , Danial Davarnia

This article describes a method to compute successive convex approximations of the convex hull of a set of points in R^n that are the solutions to a system of polynomial equations over the reals. The method relies on sums of squares of…

Optimization and Control · Mathematics 2010-07-27 João Gouveia , Rekha R. Thomas

This paper develops a correspondence relating convex hulls of fractional functions with those of polynomial functions over the same domain. Using this result, we develop a number of new reformulations and relaxations for fractional…

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

The numerical construction of polynomials in the product representation (as used for instance in variants of the multiboson technique) can become problematic if rounding errors induce an imprecise or even unstable evaluation of the…

High Energy Physics - Lattice · Physics 2009-10-31 B. Bunk , S. Elser , R. Frezzotti , K. Jansen

We study the question of whether parallelization in the exploration of the feasible set can be used to speed up convex optimization, in the local oracle model of computation. We show that the answer is negative for both deterministic and…

Optimization and Control · Mathematics 2019-06-21 Jelena Diakonikolas , Cristóbal Guzmán
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