Approximation by Lexicographically Maximal Solutions in Matching and Matroid Intersection Problems

TL;DR

This paper analyzes the effectiveness of lexicographically maximal solutions in weighted matching and matroid intersection problems, establishing thresholds for their approximation guarantees based on weight value dispersion.

Contribution

It precisely characterizes when lexicographically maximal solutions are optimal or approximate, introducing a threshold ratio of 2 for equivalence and approximation bounds.

Findings

Lexicographically maximal solutions are optimal when weight ratios are at least the ground set size.

A ratio less than 2 guarantees a (ratio/2)-approximation, which is proven to be tight.

The threshold ratio of 2 is exactly the point where lexicographic maximality aligns with weighted optimality.

Abstract

We study how good a lexicographically maximal solution is in the weighted matching and matroid intersection problems. A solution is lexicographically maximal if it takes as many heaviest elements as possible, and subject to this, it takes as many second heaviest elements as possible, and so on. If the distinct weight values are sufficiently dispersed, e.g., the minimum ratio of two distinct weight values is at least the ground set size, then the lexicographical maximality and the usual weighted optimality are equivalent. We show that the threshold of the ratio for this equivalence to hold is exactly $2$. Furthermore, we prove that if the ratio is less than $2$, say $\alpha$, then a lexicographically maximal solution achieves $(\alpha/2)$-approximation, and this bound is tight.