Speeding Up Dynamic Shortest-Path Algorithms

Dynamic shortest-path algorithms update the shortest paths taking into account a change in an arc weight. This paper describes a new generic technique that allows the reduction of heap sizes used by several dynamic single-destination shortest-path algorithms. For unit weight changes, the updates can...

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Bibliographic Details
Published in:INFORMS journal on computing Vol. 20; no. 2; pp. 191 - 204
Main Authors: Buriol, Luciana S, Resende, Mauricio G. C, Thorup, Mikkel
Format: Journal Article
Language:English
Published: Linthicum INFORMS 01.05.2008
Institute for Operations Research and the Management Sciences
Subjects:
Algorithms
Analysis
Dijkstra's algorithm
Dynamic programming
dynamic shortest-path algorithms
Graphs
heaps
Shortest path algorithms
Studies
trees
Trees (Graph theory)
United States
ISSN:1091-9856, 1526-5528, 1091-9856
Online Access:Get full text
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Summary:Dynamic shortest-path algorithms update the shortest paths taking into account a change in an arc weight. This paper describes a new generic technique that allows the reduction of heap sizes used by several dynamic single-destination shortest-path algorithms. For unit weight changes, the updates can be done without heaps. These reductions almost always reduce the computational times for these algorithms. In computational testing, several dynamic shortest-path algorithms with and without the heap-reduction technique are compared. Speedups of up to a factor of 1.8 were observed using the heap-reduction technique on random weight changes and of over a factor of five on unit weight changes. We compare as well with Dijkstra's algorithm, which recomputes the paths from scratch. With respect to Dijkstra's algorithm, speedups of up to five orders of magnitude are observed.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:1091-9856
1526-5528
1091-9856
DOI:10.1287/ijoc.1070.0231