Optimizing network attacks by artificial bee colony

To address the problem we propose an artificial bee colony algorithm, which is a swarm intelligence approach inspired in the foraging behaviour of honeybees. In this framework, bees produce new candidate solutions for the problem by exploring the vicinity of previous ones, called food sources. The proposed method exploits useful problem knowledge in this neighbourhood exploration by considering the partial destruction and heuristic reconstruction of selected solutions. The performance of the method, with respect to other models from the literature that can be adapted to face this problem, such as sequential centrality-based attacks, module-based attacks, a genetic algorithm, a simulated annealing approach, and a variable neighbourhood search, is empirically shown.