Abstract
Most of the critical infrastructures can be easily modeled as a network of nodes interconnected among them. If one or more nodes of the network fail, the connectivity of the network can be compromised, to the point of completely disconnecting the network. Additionally, disconnecting the network can result in cascade failures, because the remaining nodes may be overloaded because of heavy traffic in the network. One of the main objectives of an attacker is to isolate the nodes whose removal disconnect the network in minimum size subnetworks. On the contrary, a defender must identify those weak points in order to maintain the network integrity. This work is focused on solving the \( \alpha \) separator problem, whose main objective is to find a minimum set of nodes that disconnect a network in isolated subnetworks of size smaller than a given value. The problem is tackled from a metaheuristic point of view, analyzing the solutions given by a Greedy Randomized Adaptive Search Procedure over different network topologies. The results obtained are compared with the best algorithm found in the literature.
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This work has been partially founded by Ministerio de Economía y Competitividad with grant ref. TIN2015-65460-C2-2-P.
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Pérez-Peló, S., Sánchez-Oro, J., Duarte, A. (2018). A Metaheuristic Approach for the \( \alpha \)-separator Problem. In: Yin, H., Camacho, D., Novais, P., Tallón-Ballesteros, A. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2018. IDEAL 2018. Lecture Notes in Computer Science(), vol 11315. Springer, Cham. https://doi.org/10.1007/978-3-030-03496-2_37
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