Contracting and Compressing Shortest Path Databases

9Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

Abstract

Compressed Path Databases (CPD) are powerful database driven methods for shortest path extraction in grids and in spatial networks. Yet CPDs have two main drawbacks: (1) constructing the database requires an offline all-pairs precompute, which can sometimes be prohibitive and; (2) extracting a path requires a number of database lookups equal to its number of edges, which can be costly in terms of time. In this work, we consider how CPD methods can be improved and enhanced by: (i) contracting the input graph before preprocessing and; (ii) limiting the preprocessing step to only a selected subset of graph nodes. We also describe a new bi-directional path extraction algorithm which we call CH-CPD. In a range of experiments on road networks, we show that CH-CPD substantially improves on conventional CPDs in terms of preprocessing costs and online performance. We also report convincing query time improvements against a range of methods from the recent literature.

Cite

CITATION STYLE

APA

Shen, B., Cheema, M. A., Harabor, D. D., & Stuckey, P. J. (2021). Contracting and Compressing Shortest Path Databases. In Proceedings International Conference on Automated Planning and Scheduling, ICAPS (Vol. 2021-August, pp. 322–330). Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/icaps.v31i1.15977

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free