OASIcs.ATMOS.2021.7.pdf
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Optimal Forks: Preprocessing Single-Source Shortest Path Instances with Interval Data
Authors
Niels Lindner 
,
Pedro Maristany de las Casas ,
Philine Schiewe
-
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Volume:
21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021)
Series: Open Access Series in Informatics (OASIcs)
Conference: Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2021-09-27
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Acknowledgements
We thank Lufthansa Systems GmbH & Co. KG. and in particular Marco Blanco for the data required to build the instance representing the airway network over Germany.
Cite AsGet BibTex
Niels Lindner, Pedro Maristany de las Casas, and Philine Schiewe. Optimal Forks: Preprocessing Single-Source Shortest Path Instances with Interval Data. In 21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021). Open Access Series in Informatics (OASIcs), Volume 96, pp. 7:1-7:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/OASIcs.ATMOS.2021.7
https://doi.org/10.4230/OASIcs.ATMOS.2021.7
Abstract
We investigate preprocessing for single-source shortest path queries in digraphs, where arc costs are only known to lie in an interval. More precisely, we want to decide for each arc whether it is part of some shortest path tree for some realization of costs. We show that this problem is solvable in polynomial time by giving a combinatorial algorithm, using optimal structures that we call forks. Our algorithm turns out to be very efficient in practice, and is sometimes even superior in quality to a heuristic developed for the one-to-one shortest path problem in the context of passenger routing in public transport.
Subject Classification
ACM Subject Classification
- Mathematics of computing → Paths and connectivity problems
- Theory of computation → Shortest paths
- Mathematics of computing → Graph algorithms
Keywords
- Preprocessing Shortest Path Problems
- Interval Data
- Graph Algorithms
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References
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