Models, algorithms and technologies for network analysis : NET 2014, Nizhny Novgorod, Russia, May 2014 /

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Bibliographic Details
Meeting name:International Conference on Network Analysis (4th : 2014 : Nizhny Novgorod, Russia)
Imprint:Switzerland : Springer, [2016]
Description:1 online resource
Language:English
Series:Springer proceedings in mathematics & statistics ; volume 156
Springer proceedings in mathematics & statistics ; v. 156.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11268095
Hidden Bibliographic Details
Other authors / contributors:Kalyagin, Valery A., editor.
Koldanov, P. A., editor.
Pardalos, P. M. (Panos M.), 1954- editor.
ISBN:9783319296081
3319296086
331929606X
9783319296067
Digital file characteristics:text file PDF
Notes:Includes bibliographical references and index.
Online resource; title from PDF title page (EBSCO, viewed October 26, 2016).
Summary:The contributions in this volume cover a broad range of topics including maximum cliques, graph coloring, data mining, brain networks, Steiner forest, logistic and supply chain networks. Network algorithms and their applications to market graphs, manufacturing problems, internet networks and social networks are highlighted. The "Fourth International Conference in Network Analysis," held at the Higher School of Economics, Nizhny Novgorod in May 2014, initiated joint research between scientists, engineers and researchers from academia, industry and government; the major results of conference participants have been reviewed and collected in this Work. 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.
Other form:Print version: Models, algorithms and technologies for network analysis. [Place of publication not identified] : Springer, 2016 331929606X
Standard no.:10.1007/978-3-319-29608-1
Table of Contents:
  • Preface; References; Contents; Contributors; Part I Optimization in Networks; Maximally Diverse Grouping and Clique Partitioning Problems with Skewed General Variable Neighborhood Search; 1 Introduction; 2 Relation Between CPP and MDGP; 3 Solving MDGP with Variable Neighborhood Search; 3.1 Solution Space of MDGP; 3.2 VND Local Search; 3.3 Initial Solution; 3.4 Shaking; 3.5 Skewed General Variable Neighborhood Search; 4 Implementation Differences for Solving CPP with SGVNS; 5 Computational Results for MDGP; 5.1 VNS Parameter Values; 5.2 Comparison of Average Results.
  • 6 Computational Results for CPP7 Conclusions; References; Test Generation for Digital Circuits Based on Continuous Approach to Circuit Simulation Using Different Continuous Extensions of Boolean Functions; 1 Introduction; 2 Continuous Approach of Digital Circuits Simulation; 3 Test Pattern Generation Algorithm; 4 Investigation of Various Continuous Models of Boolean Functions for Test Generation; 5 Results; 6 Conclusion; References; König Graphs for 4-Paths: Widened Cycles; 1 Introduction; 2 Some Definitions; 3 Widened Subdivisions of Even Cycles; 4 The Main Theorem; References.
  • Optimization Algorithms for Shared Groups in Multicast Routing; 1 Introduction; 1.1 Problem Formulation; 2 Literature Review; 2.1 Center-Based Approaches; 2.2 Mathematical Programming Formulation; 2.3 Distributed Algorithms for MGR; 3 Heuristics for Multicast Group Routing; 3.1 Tree Connection Heuristic; 3.2 Combined Shortest Path Heuristic; 4 Computational Results; 5 Concluding Remarks; References; Minimizing the Fuel Consumption of a Multiobjective Vehicle Routing Problem Using the Parallel Multi-Start NSGA II Algorithm; 1 Introduction.
  • 2 Multiobjective Fuel Consumption Vehicle Routing Problem; 3 Parallel Multi-Start NSGA II Algorithm; 4 Evaluation Measures; 5 Computational Results; 6 Conclusions and Future Research; References; Manifold Location Routing Problem with Applications in Network Theory; 1 Introduction; 2 Riemannian Manifolds and Geodesic Distances; 3 MLRP Algorithmic Solution: Single-Facility Case; 3.1 Algorithmic Solution for 1-MLRP ; 3.2 Computational Complexity; 3.3 Algorithmic Solution Steps to Solve 1-MLRP; 3.4 Facility Locations on R2; 3.5 Projection from R2 to M.
  • 4 Manifold Location Routing Problem: 2-Facility Case; 4.1 Statement of 2-MLRP; 5 Solution Methodology for 2-MLRP; 5.1 Main Steps of the Heuristic Algorithm; 5.2 Heuristic Algorithm for the Proposed 2-MLRP; 5.3 Computational Complexity; 5.4 Algorithmic Solution Details of 2-MLRP; 5.4.1 Projections from M to R2; 5.4.2 Initial Facility Locations and LCM: Heuristic Solution; 5.4.3 Mapping from R2 to M; 6 Applications in Network Theory; 7 Summary; References; A Branch and Bound Algorithm for the Cell Formation Problem; 1 Introduction; 2 Formulation; 3 Objective Functions; 4 Definitions.