Iteratively reweighted greedy set cover

TL;DR

This paper presents an iterative, parameter-free heuristic based on weighted greedy algorithms for large sparse set cover problems, demonstrating that multiple iterations improve solutions efficiently.

Contribution

It introduces a simple, effective iterative reweighting approach for greedy set cover, with minimal tuning and practical applicability.

Findings

Multiple iterations improve solution quality.

Algorithm is trivial to implement and parameter-free.

Suitable for large sparse set cover problems.

Abstract

We empirically analyze a simple heuristic for large sparse set cover problems. It uses the weighted greedy algorithm as a basic building block. By multiplicative updates of the weights attached to the elements, the greedy solution is iteratively improved. The implementation of this algorithm is trivial and the algorithm is essentially free of parameters that would require tuning. More iterations can only improve the solution. This set of features makes the approach attractive for practical problems.