  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 paper, we propose a cost-effective targeted
enumeration method for network disintegration. The proposed approach includes
two stages: searching for candidate objects and 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 trade-off between effectiveness and
efficiency. The introduced two-stage targeted enumeration framework can also be
applied to other computationally intractable combinational optimization
problems, from team assembly via portfolio investment to drug design.
