# Global Sensitivity Analysis for the Linear Assignment Problem

arXiv: https://arxiv.org/abs/2005.11792 · HTML: https://mlsanity.com/paper/2005.11792/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 May 2020.

## Built on by (most cited first, 1 of 1)

- [DAG Learning on the Permutahedron](https://mlsanity.com/paper/2301.11898/) (2023)

## Abstract (arXiv)

In this paper, the following question is addressed: given a linear assignment problem, how much can the all of the individual assignment weights be perturbed without changing the optimal assignment? The extension of results involving perturbations in just one edge or one row/column are presented. Algorithms for the derivation of these bounds are provided. We also show how these bounds may be used to prevent assignment churning in a multi-vehicle guidance scenario.