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Models, Algorithms and Technologies for Network Analysis

From the Third International Conference on Network Analysis

  • Conference proceedings
  • © 2014

Overview

Editors:
  1. Mikhail V. Batsyn

    1. Laboratory of Algorithms and Technologies for Networks Analysis, Department of Applied Mathematics and Informatics, National Research University Higher School of Economics, Nizhny Novgorod, Russia

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  2. Valery A. Kalyagin

    1. Laboratory of Algorithms and Technologies for Networks Analysis, Department of Applied Mathematics and Informatics, National Research University Higher School of Economics, Nizhny Novgorod, Russia

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  3. Panos M. Pardalos

    1. Laboratory of Algorithms and Technologies for Networks Analysis, Department of Industrial and Systems Engineering, Center for Applied Optimization, National Research University Higher School of Economics, Nizhny Novgorod, Russia, University of Florida, Gainesville, USA

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  • Network analysis is a powerful method which can be used to solve manufacturing, transportation, economic, and other applied problems
  • Analysis of the reliability of complex networks is necessary for power, communication, and transport networks and is widely applied in power supply systems, military sphere, and emergency evacuation planning
  • Contains novel algorithms and technologies for network analysis
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 104)

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Table of contents (11 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. A Method of Static and Dynamic Pattern Analysis of Innovative Development of Russian Regions in the Long Run

    • Fuad Aleskerov, Ludmila Egorova, Leonid Gokhberg, Alexey Myachin, Galina Sagieva
    Pages 1-8

  3. Using Mathematical Programming to Refine Heuristic Solutions for Network Clustering

    • Sonia Cafieri, Pierre Hansen
    Pages 9-20

  4. Market Graph Construction Using the Performance Measure of Similarity

    • Andrey A. Glotov, Valery A. Kalyagin, Arsenii N. Vizgunov, Panos M. Pardalos
    Pages 21-35

  5. The Flatness Theorem for Some Class of Polytopes and Searching an Integer Point

    • Dmitry V. Gribanov
    Pages 37-43

  6. How Independent Are Stocks in an Independent Set of a Market Graph

    • Petr A. Koldanov, Ivan Grechikhin
    Pages 45-53

  7. Analysis of Russian Industries in the Stock Market

    • Nina N. Lozgacheva, Alexander P. Koldanov
    Pages 55-68

  8. A Particle Swarm Optimization Algorithm for the Multicast Routing Problem

    • Yannis Marinakis, Athanasios Migdalas
    Pages 69-91

  9. König Graphs for 4-Paths

    • Dmitry Mokeev
    Pages 93-103

  10. A Hybrid Metaheuristic for Routing on Multicast Networks

    • Carlos A. S. Oliveira, Panos M. Pardalos
    Pages 105-118

  11. Possible Ways of Applying Citations Network Analysis to a Scientific Writing Assistant

    • Alexander Porshnev, Maxim Kazakov
    Pages 119-126

  12. Bounding Fronts in Multi-Objective Combinatorial Optimization with Application to Aesthetic Drawing of Business Process Diagrams

    • Julius Žilinskas, Antanas Žilinskas
    Pages 127-139
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Keywords

About this book

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.

Editors and Affiliations

  • Laboratory of Algorithms and Technologies for Networks Analysis, Department of Applied Mathematics and Informatics, National Research University Higher School of Economics, Nizhny Novgorod, Russia

    Mikhail V. Batsyn, Valery A. Kalyagin

  • Laboratory of Algorithms and Technologies for Networks Analysis, Department of Industrial and Systems Engineering, Center for Applied Optimization, National Research University Higher School of Economics, Nizhny Novgorod, Russia, University of Florida, Gainesville, USA

    Panos M. Pardalos

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