K* : heuristics-guided, on-the-fly k shortest paths search

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We present a search algorithm, called K*, for finding the k shortest paths (KSP) between a designated pair of vertices in a given directed weighted graph. As a directed algorithm, K* has two advantages compared to current KSP algorithms. First, K* performs on-the-fly, which means that it does not require the graph to be explicitly available and stored in main memory. Portions of the graph will be generated as needed. Second, K* can be guided using heuristic functions. We discuss the properties of K*, including its correctness, and its asymptotic worst-case complexity, which has been shown to be of O(m+n log n+k) with respect to both runtime and space, where n is the number of vertices and m is the number of edges of the graph. We report on experimental results which illustrate the favorable performance of K* compared to the most efficient k-shortest-paths algorithms known so far. In other work it has been shown that K* can be used to efficiently compute counterexamples for stochastic model checking.

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ISO 690ALJAZZAR, Husain, Stefan LEUE, 2010. K* : heuristics-guided, on-the-fly k shortest paths search
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@inproceedings{Aljazzar2010heuri-21288,
  year={2010},
  title={K* : heuristics-guided, on-the-fly k shortest paths search},
  author={Aljazzar, Husain and Leue, Stefan},
  note={Paper presented at: Sixth Workshop on Model Checking and Artificial Intelligence (MoChArt) 2010}
}
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Paper presented at: Sixth Workshop on Model Checking and Artificial Intelligence (MoChArt) 2010
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