Disintegrating spatial networks based on region centrality

Finding an optimal strategy at a minimum cost to efficiently disintegrate a harmful network into isolated components is an important and interesting problem, with applications in particular to anti-terrorism measures and epidemic control. This paper focuses on optimal disintegration strategies for spatial networks, aiming to find an appropriate set of nodes or links whose removal would result in maximal network fragmentation. We refer to the sum of the degree of nodes and the number of links in a specific region as region centrality. This metric provides a comprehensive account of both topological properties and geographic structure. Numerical experiments on both synthetic and real-world networks demonstrate that the strategy is significantly superior to conventional methods in terms of both effectiveness and efficiency. Moreover, our strategy tends to cover those nodes close to the average degree of the network rather than concentrating on nodes with higher centrality.