Abstract

We consider the critical node detection problem (CNDP) in directed graphs, which can be defined as follows. Given a directed graph G and a parameter k , we wish to remove a subset S of at most k vertices of G such that the residual graph G ∖ S has minimum pairwise strong connectivity. This problem is NP-hard, and thus we are interested in practical heuristics. In this article, we apply the framework of Georgiadis et al. (SODA 2017) and provide a sophisticated linear-time algorithm for the k =1 case. Based on this algorithm, we provide an efficient heuristic for the general case. Then, we conduct a thorough experimental evaluation of various heuristics for CNDP. Our experimental results suggest that our heuristic performs very well in practice, both in terms of running time and of solution quality.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.