Editors:
- Presents state-of-the-art techniques in modern network analysis for large-scale networks
- Features new theoretical models, approaches, and tools for network analysis
- Broadens understanding of computationally efficient algorithms
Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 247)
Conference series link(s): NET: International Conference on Network Analysis
Conference proceedings info: NET 2018.
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Table of contents (26 papers)
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Front Matter
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Network Computational Algorithms
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Front Matter
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Network Models
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Front Matter
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Other Volumes
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Computational Aspects and Applications in Large-Scale Networks
About this book
Contributions in this volume focus on computationally efficient algorithms and rigorous mathematical theories for analyzing large-scale networks. Researchers and students in mathematics, economics, statistics, computer science and engineering will find this collection a valuable resource filled with the latest research in network analysis. Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks.
This proceeding is a result of the 7th International Conference in Network Analysis, held at the Higher School of Economics, Nizhny Novgorod in June 2017. The conference brought together scientists, engineers, and researchers from academia, industry, and government.Keywords
- Computational Aspects and Applications of Large Scale Networks
- Critical Links
- Autoregressive Models
- Equilibrium Under Network Constraints
- Cliques
- Quasi-cliques
- Clustering Coefficient
- Random Graphs
- Guarantee Networks
- Neural Network
- Complexity of Graphs
- Vehicle Routing Problems
- triangle-Konig Graphs
- Integer Linear Programming Problems
- Bilevel Pricing Problem
- Graph Dichotomy Algorithm
- Network Analysis
- Gaussian Graphical Model
- Topological Structure Formation
- combinatorics
Editors and Affiliations
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Higher School of Economics, National Research University, Nizhny Novgorod, Russia
Valery A. Kalyagin, Irina Utkina
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Department of Industrial and Systems Engineering, University of Florida, Gainesville, USA
Panos M. Pardalos
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Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, USA
Oleg Prokopyev
Bibliographic Information
Book Title: Computational Aspects and Applications in Large-Scale Networks
Book Subtitle: NET 2017, Nizhny Novgorod, Russia, June 2017
Editors: Valery A. Kalyagin, Panos M. Pardalos, Oleg Prokopyev, Irina Utkina
Series Title: Springer Proceedings in Mathematics & Statistics
DOI: https://doi.org/10.1007/978-3-319-96247-4
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-96246-7Published: 25 August 2018
Softcover ISBN: 978-3-030-07163-9Published: 31 January 2019
eBook ISBN: 978-3-319-96247-4Published: 24 August 2018
Series ISSN: 2194-1009
Series E-ISSN: 2194-1017
Edition Number: 1
Number of Pages: XVII, 354
Number of Illustrations: 27 b/w illustrations, 41 illustrations in colour
Topics: Operations Research, Management Science, Mathematical Models of Cognitive Processes and Neural Networks, Combinatorics, Probability Theory and Stochastic Processes