Generating Random Networks Without Short Cycles

OPERATIONS RESEARCH, pp. 1227-1246, 2018.

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Abstract:

Random graph generation is an important tool for studying large complex networks. Despite abundance of random graph models, constructing models with application-driven constraints is poorly understood. To advance state-of-the-art in this area, we focus on random graphs without short cycles as a stylized family of graphs, and we propose th...More

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