@inproceedings{a2101b8f259d46fa81fcc0978c5f991c,

title = "Numerical optimization of generative network parameters",

abstract = "We address the design of complex, large-scale systems by viewing them as random networks, and optimizing network structure over generative parameters. We do not seek specific topologies, but rather classes of optimal or near optimal networks which correspond to desirable statistical behavior, while also allowing flexibility to accommodate unmodeled constraints. This approach is a computationally feasible forward design path for large-scale systems. A numerical example is given in which a network's degree distribution is optimized for combined efficiency and robustness in a cascading failure scenario; the work has application to electric distribution and other systems.",

keywords = "Cascading failure, Clustering, Configuration model, Particle swarm optimization, Random network",

author = "Taylor, {Joshua A.} and Hover, {Franz S.}",

year = "2010",

language = "English (US)",

isbn = "9781617387043",

series = "Grand Challenges in Modeling and Simulation Symposium, GCMS 2010 - Proceedings of the 2010 Summer Simulation Multiconference, SummerSim 2010",

number = "3 BOOK",

pages = "66--71",

booktitle = "Grand Challenges in Modeling and Simulation Symposium, GCMS 2010 - Proceedings of the 2010 Summer Simulation Multiconference, SummerSim 2010",

edition = "3 BOOK",

note = "Grand Challenges in Modeling and Simulation Symposium, GCMS 2010, Part of the 2010 Summer Simulation Multiconference, SummerSim 2010 ; Conference date: 12-07-2010 Through 14-07-2010",

}