A Neural-network Algorithm for All k Shortest Paths Problem

Authors:
Kun Zhao;Abdoul Sylla
Affiliations:
Department of Mathematics and Statistics, Georgia State University, Atlanta, Georgia 30303;Enterprise Architecture, Travelport Inc., 300 Galleria Pkwy SE #400 Atlanta, GA 30339
Venue:
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
Year:
2013

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Abstract

One of the fundamental computations for network analysis is to calculate the shortest path (SP) and all k shortest paths (KSP) between two nodes. Finding SP and KSP in a large graph is not trivial since the computation time increases as the number of nodes and edges increases. A recent neural network algorithm for calculating SP showed its advantage of not depending on the number of nodes and edges but the topology of a graph. Reasonable performance of the algorithm was reported. However, this algorithm is limited to the SP problem. This paper reports the progress of extending a neural network algorithm to solve the KSP problem. How to apply the new KSP algorithm to a whole-genome sequencing problem is also discussed.