Affiliation:
1. Karlsruhe Institute of Technology
Abstract
We consider the problem of quickly computing shortest paths in weighted graphs. Often, this is achieved in two phases: (1) derive auxiliary data in an expensive preprocessing phase, and (2) use this auxiliary data to speed up the query phase. By adding a fast weight-customization phase, we extend Contraction Hierarchies to support a three-phase workflow. The expensive preprocessing is split into a phase exploiting solely the unweighted topology of the graph and a lightweight phase that adapts the auxiliary data to a specific weight. We achieve this by basing our Customizable Contraction Hierarchies (CCHs) on nested dissection orders. We provide an in-depth experimental analysis on large road and game maps showing that CCHs are a very practicable solution in scenarios where edge weights often change.
Funder
Google Focused Research Award
DFG
EU
Publisher
Association for Computing Machinery (ACM)
Subject
Theoretical Computer Science
Cited by
33 articles.
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