Cost-Effective Network Disintegration Through Targeted Enumeration
提出一种两阶段目标枚举方法，先聚合节点重要性排名缩小候选集，再枚举最优组合，在合成和真实网络上实现了效果与效率的平衡，适用于反恐、流行病控制等场景。
Finding an optimal subset of nodes or links to disintegrate harmful networks is a fundamental problem in network science, with potential applications to anti-terrorism, epidemic control, and many other fields of study. The challenge of the network disintegration problem is to balance the effectiveness and efficiency of strategies. In this article, we propose a cost-effective targeted enumeration (TE) method for network disintegration. The proposed approach includes two stages: 1) searching for candidate objects and 2) identifying an optimal solution. In the first stage, we use rank aggregation to generate a comprehensive ranking of node importance, upon which we identify a small-scale candidate set of nodes to remove. In the second stage, we use an enumeration method to find an optimal combination among the candidate nodes. Extensive experimental results on synthetic and real-world networks demonstrate that the proposed method achieves a satisfying tradeoff between effectiveness and efficiency. Our adaptable TE approach can effectively address a range of combinatorial optimization challenges with significant potential applications, including personnel recruitment, portfolio management, and pharmaceutical development.