Models, Algorithms and Technologies for Network Analysis [electronic resource] : From the Third International Conference on Network Analysis / edited by Mikhail V. Batsyn, Valery A. Kalyagin, Panos M. Pardalos
- Batsyn, Mikhail
- Cham : Springer International Publishing : Imprint: Springer, 2014.
- Physical Description:
- X, 139 pages 41 illustrations, 23 illustrations in color : online resource
- Additional Creators:
- Kalyagin, Valery A., Pardalos, P. M. (Panos M.), 1954-, and SpringerLink (Online service)
- Springer Proceedings in Mathematics & Statistics, 2194-1009 ; 104
- A method of static and dynamic pattern analysis of innovative development of Russian regions in the long run -- Using mathematical programming to refine heuristic solutions for network clustering -- Market graph construction using the performance measure of similarity -- How independent are stocks in an independent set of a market graph -- Analysis of Russian industries in the stock market -- A particle swarm optimization algorithm for the multicast routing problem -- König graphs for 4-paths -- A hybrid metaheuristic for routing on multicast networks -- Possible ways of applying citations network analysis to a scientific writing assistant -- Bounding fronts in multi-objective combinatorial optimization with application to aesthetic drawing of business process diagrams.
- This volume compiles the major results of conference participants from the "Third International Conference in Network Analysis" held at the Higher School of Economics, Nizhny Novgorod in May 2013, with the aim to initiate further joint research among different groups. The contributions in this book cover a broad range of topics relevant to the theory and practice of network analysis, including the reliability of complex networks, software, theory, methodology, and applications. Network analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network has brought together researchers, practitioners from numerous fields such as operations research, computer science, transportation, energy, biomedicine, computational neuroscience and social sciences. In addition, new approaches and computer environments such as parallel computing, grid computing, cloud computing, and quantum computing have helped to solve large scale network optimization problems.
- Digital File Characteristics:
- text file PDF
- AVAILABLE ONLINE TO AUTHORIZED PSU USERS.
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