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- W2963003535 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 the RandGraph algorithm for randomly generating them. For any constant k, when m = O(n 1+1/[2k(k+3)] ), RandGraph generates an asymptotically uniform random graph with n vertices, m edges, and no cycle of length at most k using O(n 2 m) operations. We also characterize the approximation error for finite values of n. To the best of our knowledge, this is the first polynomial-time algorithm for the problem. RandGraph works by sequentially adding m edges to an empty graph with n vertices. Recently, such sequential algorithms have been successful for random sampling problems. Our main contributions to this line of research include introducing a new approach for sequentially approximating edge-specific probabilities at each step of the algorithm and providing a new method for analyzing such algorithms." @default.
- W2963003535 created "2019-07-30" @default.
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- W2963003535 date "2018-10-01" @default.
- W2963003535 modified "2023-10-14" @default.
- W2963003535 title "Generating Random Networks Without Short Cycles" @default.
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- W2963003535 doi "https://doi.org/10.1287/opre.2018.1730" @default.
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