A multi-agent genetic algorithm for improving the robustness of communities in complex networks against attacks

The design of robust networked structures is of significance in reality, and the integrity of network connections has been greatly emphasized in previous studies. However, besides structural integrity, a system should also keep the functionality when suffering from attacks and failures, i.e. robust community structure. Focusing on enhancing community robustness on complex networks, in this paper, based on a community robustness measure Rc, a multi-agent genetic algorithm, termed as MAGA-Rc, has been proposed to enhance the community robustness against attacks. The performance of MAGA-Rc is validated on several real-world networks, and the results show that MAGA-Rc could deal with the optimization of community robustness and outperforms several existing methods. The results provide convenience for networked property analyses and applicable to solve realistic optimization problems.