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Modelling and Data Analysis
2020. Vol. 10, no. 3, 60–68
https://doi.org/10.17759/mda.2020100305
ISSN: 2219-3758 / 2311-9454 (online)

Practical Realization of Algorithm of Oriented Graph Paths Decomposition

 
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Abstract

This study aims to clarify the methodological status program realization of oriented graph paths decomposition. Algorithms of matrix formulation of decomposition table M from multitude of paths, table sorting by NΣ and balance computing explored. On the basis of those algorithms and original algorithm of oriented graph paths decomposition realized Python 3 program. Results for random-generated graph size of 100 vertices computed and time measured. The results obtained can be used to solve the problem of organizing freight rail transportation at the stage of assignment and movement of locomotives. The scientifi c and practical novelty of the work lies in a signifi cant reduction in the dimension of the original problem, which is especially important in the conditions of transport networks of complex topology.

General Information

Keywords: optimization theory, graph optimization, algorithm of directed graph paths decomposition, strongly connected graph, subgraphs

Journal rubric: Optimization Methods

OpenAlex citations: 2

OpenAlex trends: Transport and Logistics Innovations, Transportation Systems and Logistics, Urban Transport Systems Analysis

Information about the work in OpenAlex

Number of citations: 2

Topics

Transport and Logistics Innovations

This cluster of papers focuses on various aspects of transportation and logistics management, including logistics systems design, sustainable human resource management, digitalization, supply chain optimization, and railway transportation. It explores topics such as the impact of human resource management on competitiveness, sustainability in globalized transportation, and the application of digital technologies for knowledge sharing and smart maintenance. The cluster reflects a multidisciplinary approach to addressing challenges and opportunities in the transportation and logistics sector.

Number of works: 51786  |  Total number of citations: 39486

Topic detailsв OpenAlex

Transportation Systems and Logistics

This cluster of papers focuses on the development and improvement of traffic safety systems and infrastructure, including intelligent transportation systems, road infrastructure, vehicle diagnostics, traffic management, and the environmental impact of transportation. It addresses topics such as accident reconstruction, digital technologies in transportation, and the impact of operational factors on environmental safety.

Number of works: 24013  |  Total number of citations: 38397

Topic detailsв OpenAlex

Urban Transport Systems Analysis

This cluster of papers focuses on the planning, modeling, and management of transportation systems, with an emphasis on digital technologies, quality management, urban traffic, dependability, infrastructure, logistics, and cyber security.

Number of works: 46745  |  Total number of citations: 43271

Topic detailsв OpenAlex

Work details in OpenAlex

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2020100305

Published

For citation: Zolotarev, I.A., Rasskazova, V.A. (2020). Practical Realization of Algorithm of Oriented Graph Paths Decomposition. Modelling and Data Analysis, 10(3), 60–68. (In Russ.). https://doi.org/10.17759/mda.2020100305

© Zolotarev I.A., Rasskazova V.A., 2020

License: CC BY-NC 4.0

References

  1. Gainanov D.N., Konygin A.V., Rasskazova V.A. Modelling railway freight traffi c using the methods of graph theory and combinatorial optimization. Automation and Remote Control, 2016 vol. 77, no. 11, pp. 1928–1943.
  2. Gainanov D.N., Kibzun A.I., Rasskazova V.A. Theoretical-graph algorithm in the problem on the assignments and transportations of locomotives. Herald of computer and information technologies, 2017, no. 5, pp. 51–56.
  3. Gainanov D.N., Kibzun A.I., Rasskazova V.A. The Decomposition Problem for the Set of Paths in a Directed Graph and Its Application. Automation and Remote Control, 2018, vol. 79, no. 12, pp. 2217–2236.

Information About the Authors

Igor A. Zolotarev, Master's Student, Moscow Aviation Institute (NRU MAI), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-6437-2212, e-mail: yngvar.antonsson@gmail.com

Varvara A. Rasskazova, Candidate of Science (Physics and Matematics), Associate Professor of Department 804 "Probability Theory and Computer Modeling", Moscow Aviation Institute, (NRU MAI), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0003-4943-3133, e-mail: varvara.rasskazova@mail.ru

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