Arc-Search Infeasible Interior-Point Algorithm for Linear Programming

TL;DR

This paper introduces an arc-search infeasible interior-point algorithm for linear programming, demonstrating through tests on Netlib problems that it outperforms the widely used Mehrotra's algorithm in efficiency.

Contribution

The paper proposes a novel arc-search infeasible interior-point algorithm that improves efficiency over the traditional Mehrotra's algorithm for linear programming.

Findings

Arc-search algorithm is more efficient than Mehrotra's algorithm.

Test results on Netlib problems show improved performance.

The new method maintains robustness across various problem instances.

Abstract

Mehrotra's algorithm has been the most successful infeasible interior-point algorithm for linear programming since 1990. Most popular interior-point software packages for linear programming are based on Mehrotra's algorithm. This paper proposes an alternative algorithm, arc-search infeasible interior-point algorithm. We will demonstrate, by testing Netlib problems and comparing the test results obtained by arc-search infeasible interior-point algorithm and Mehrotra's algorithm, that the proposed arc-search infeasible interior-point algorithm is a more efficient algorithm than Mehrotra's algorithm.