An elitism-based multi-objective evolutionary algorithm for min-cost network disintegration

Network disintegration or strengthening is a significant problem, which widely used in infrastructure construction, social networks, infectious disease prevention and so on. But most studies assume that the cost of attacking anyone node equal. In this paper, we investigate robustness complex networks under more realistic assumption costs are functions degrees nodes. A multi-objective, elitism-based, evolutionary algorithm (MOEEA) proposed for network problem with heterogeneous costs. By defining new unit influence measure target attack combining an elitism strategy, some combination nodes’ information can be retained. Through ingenious update mechanism, passed on to next generation guide population move promising regions, improve rate convergence algorithm. series experiments have been carried out four benchmark model results show our method performs better than five other state-of-the-art strategies. MOEEA usually find min-cost solutions. Simultaneously, through testing different functions, stronger heterogeneity, performance