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Designing networks: A mixed-integer linear optimization approach

Author(s): Gounaris, Chrysanthos E.; Rajendran, Karthikeyan; Kevrekidis, Yannis G.; Floudas, Christodoulos A.

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Abstract: Designing networks with specified collective properties is useful in a variety of application areas, enabling the study of how given properties affect the behavior of network models, the downscaling of empirical networks to workable sizes, and the analysis of network evolution. Despite the importance of the task, there currently exists a gap in our ability to systematically generate networks that adhere to theoretical guarantees for the given property specifications. In this paper, we propose the use of Mixed-Integer Linear Optimization modeling and solution methodologies to address this Network Generation Problem. We present a number of useful modeling techniques and apply them to mathematically express and constrain network properties in the context of an optimization formulation. We then develop complete formulations for the generation of networks that attain specified levels of connectivity, spread, assortativity and robustness, and we illustrate these via a number of computational case studies.
Publication Date: Dec-2016
Electronic Publication Date: 18-Aug-2016
Citation: Gounaris, Chrysanthos E, Rajendran, Karthikeyan, Kevrekidis, Yannis G, Floudas, Christodoulos A. (2016). Designing networks: A mixed-integer linear optimization approach. Networks, 68 (4), 283 - 301. doi:10.1002/net.21699
DOI: doi:10.1002/net.21699
ISSN: 0028-3045
Pages: 283 - 301
Type of Material: Journal Article
Journal/Proceeding Title: Networks
Version: Author's manuscript

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