Abstract In this paper we devise a generative random network model with core–periphery properties whose core nodes act as sublinear dominators , that is, if the has n nodes, size o ( ) and dominates entire network. We show instances generated by exhibit power law degree distributions, incorporates small-world phenomena. also fit our in variety of real-world networks.

Abstract There are many reasons to reform the Stability and Growth Pact, but that is no panacea. This because euro area periphery has increasingly entered a debt conundrum.

A popular objective criterion for partitioning a set of actors into core and periphery subsets is the maximization of the correlation between an ideal and observed structure associated with intra-core and intra-periphery ties. The resulting optimization problem has commonly been tackled using heuristic procedures such as relocation algorithms, genetic algorithms, and simulated annealing. In thi...