http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Models, algorithms and technologies for network analysis
NET 2014, Nizhny Novgorod, Russia, May 2014
International Conference on Network Analysis 2014 : Nizhny Novgorod, Russia)
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 Routing1 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 Problem3 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 Case4.1 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
Valery A. Kalyagin, Petr A. Koldanov, Panos M. Pardalos, editors.
Includes bibliographical references and index.
[Place of publication not identified] : Springer, 2016
Springer proceedings in mathematics & statistics ; v. 156