Accelerate Incremental TSP Algorithms on Time Evolving Graphs with Partitioning Methods

In time-evolving graphs, the graph changes at each time interval, and the previously computed results become invalid. We addressed this issue for the traveling salesman problem (TSP) in our previous work and proposed an incremental algorithm where the TSP tour is computed from the previous result in...

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Bibliographic Details
Published in:Algorithms Vol. 15; no. 2; p. 64
Main Authors: Sharma, Shalini, Chou, Jerry
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.02.2022
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ISSN:1999-4893, 1999-4893
Online Access:Get full text
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Summary:In time-evolving graphs, the graph changes at each time interval, and the previously computed results become invalid. We addressed this issue for the traveling salesman problem (TSP) in our previous work and proposed an incremental algorithm where the TSP tour is computed from the previous result instead of the whole graph. In our current work, we have mapped the TSP problem to three partitioning methods named vertex size attribute, edge attribute, and k-means; then, we compared the TSP tour results. We have also examined the effect of increasing the number of partitions on the total computation time. Through our experiments, we have observed that the vertex size attribute performs the best because of a balanced number of vertices in each partition.
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ISSN:1999-4893
1999-4893
DOI:10.3390/a15020064