Exact Minimum Weight Spanners via Column Generation

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Bökler, Fritz, Chimani, Markus, Jasper, Henning, Wagner, Mirko H.
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866910504419590144
author Bökler, Fritz
Chimani, Markus
Jasper, Henning
Wagner, Mirko H.
author_facet Bökler, Fritz
Chimani, Markus
Jasper, Henning
Wagner, Mirko H.
contents Given a weighted graph $G$, a minimum weight $α$-spanner is a least-weight subgraph $H\subseteq G$ that preserves minimum distances between all node pairs up to a factor of $α$. There are many results on heuristics and approximation algorithms, including a recent investigation of their practical performance [20]. Exact approaches, in contrast, have long been denounced as impractical: The first exact ILP (integer linear program) method [48] from 2004 is based on a model with exponentially many path variables, solved via column generation. A second approach [2], modeling via arc-based multicommodity flow, was presented in 2019. In both cases, only graphs with 40-100 nodes were reported to be solvable. In this paper, we briefly report on a theoretical comparison between these two models from a polyhedral point of view, and then concentrate on improvements and engineering aspects. We evaluate their performance in a large-scale empirical study. We report that our tuned column generation approach, based on multicriteria shortest path computations, is able to solve instances with over 16000 nodes within 13 minutes. Furthermore, now knowing optimal solutions for larger graphs, we are able to investigate the quality of the strongest known heuristic on reasonably sized instances for the first time.
format Preprint
id arxiv_https___arxiv_org_abs_2406_19164
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Exact Minimum Weight Spanners via Column Generation
Bökler, Fritz
Chimani, Markus
Jasper, Henning
Wagner, Mirko H.
Data Structures and Algorithms
Discrete Mathematics
Combinatorics
68R10 (Primary) 05C85, 90C11 (Secondary)
F.2.2; G.2.1; G.2.2
Given a weighted graph $G$, a minimum weight $α$-spanner is a least-weight subgraph $H\subseteq G$ that preserves minimum distances between all node pairs up to a factor of $α$. There are many results on heuristics and approximation algorithms, including a recent investigation of their practical performance [20]. Exact approaches, in contrast, have long been denounced as impractical: The first exact ILP (integer linear program) method [48] from 2004 is based on a model with exponentially many path variables, solved via column generation. A second approach [2], modeling via arc-based multicommodity flow, was presented in 2019. In both cases, only graphs with 40-100 nodes were reported to be solvable. In this paper, we briefly report on a theoretical comparison between these two models from a polyhedral point of view, and then concentrate on improvements and engineering aspects. We evaluate their performance in a large-scale empirical study. We report that our tuned column generation approach, based on multicriteria shortest path computations, is able to solve instances with over 16000 nodes within 13 minutes. Furthermore, now knowing optimal solutions for larger graphs, we are able to investigate the quality of the strongest known heuristic on reasonably sized instances for the first time.
title Exact Minimum Weight Spanners via Column Generation
topic Data Structures and Algorithms
Discrete Mathematics
Combinatorics
68R10 (Primary) 05C85, 90C11 (Secondary)
F.2.2; G.2.1; G.2.2
url https://arxiv.org/abs/2406.19164