Contracting and Compressing Shortest Path Databases


  • Bojie Shen Monash University
  • Muhammad Aamir Cheema Monash University
  • Daniel D. Harabor Monash University
  • Peter J. Stuckey Monash University


Planning and Scheduling


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.




How to Cite

Shen, B., Cheema, M. A., Harabor, D. D., & Stuckey, P. J. (2021). Contracting and Compressing Shortest Path Databases. Proceedings of the International Conference on Automated Planning and Scheduling, 31(1), 322-330. Retrieved from