A multi-population quantum genetic algorithm for improving the robustness of interdependent networks

In real life, interdependent networks are common and their robustness has received considerable attention. When an interdependent network is attacked, the failure may propagate along the links to the whole network. Among them, adding inter-links is an effective way to improve the robustness of the network, but it becomes a challenge to achieve maximum improvement in robustness with a limited number of added links, and in real network scenarios, we may have limited information about the network. To address this problem, in this paper, we propose a multi-population quantum genetic algorithm for optimizing the link addition strategy to improve the robustness of interdependent networks against random attacks, called MPQGA. In addition, we design an effective quantum revolving gate strategy and a multi-population migration operator to find the optimal way to add links globally. In the experiments, we compare the proposed algorithm with four existing methods on two types of interdependent networks of different sizes, and the experimental results show that MPQGA performs excellently in enhancing the robustness of interdependent networks.