A Dual Approach for Solving Nonlinear Infinite-Norm Minimization Problems with Applications in Separable Cases

TL;DR

This paper introduces a dual approach for solving nonlinear infinite-norm minimization problems, providing a new algorithm applicable to mixed linear and nonlinear cases with demonstrated numerical results.

Contribution

It develops a Lagrangian dual method for nonlinear infinite-norm minimization and proposes an algorithm for mixed cases, expanding solution techniques in this area.

Findings

Effective dual approach for nonlinear infinite-norm problems

Algorithm successfully applied to mixed linear and nonlinear cases

Numerical results demonstrate practical viability

Abstract

In this paper, we focus on nonlinear infinite-norm minimization problems that have many applications, especially in computer science and operations research. We set a reliable Lagrangian dual aproach for solving this kind of problems in general, and based on this method, we propose an algorithm for the mixed linear and nonlinear infinite-norm minimization cases with numerical results.