Application of a Genetic Algorithm for Pipeline Route Design


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Abstract

This study investigates the evaluation of a new approach for the pipeline route design process using the synthesis of artificial intelligence algorithms and Earth remote sensing data. For the effective construction of gas pipelines, a thorough comprehensive analysis of various geological, environmental, economic, and infrastructural factors is necessary. Route design is based on the principle of building a trajectory with the lowest cost. For this purpose, a multifactorial analysis of the territory was conducted according to key parameters that affect the financial costs during construction. The following groups of features were identified: water barriers, geomorphological factors, existing transport routes, specially protected natural areas, and proximity to large settlements. The approach of multifactorial suitability analysis was studied and adapted, on the basis of which the cost map used in the search for the path of lowest cost was formed. The main result of this study is the obtained software solution, which provides optimization of weighting coefficients in the multifactorial analysis of territories for laying main gas pipelines based on a genetic algorithm. The advantages of the proposed approach are the automation of the process and consideration of the regional characteristics of the territories. As a practical application, trajectories have been developed to solve the problem of gasification in the Krasnoyarsk Territory of the Russian Federation.

About the authors

Vasily K. Lobanov

RUDN University

Email: lobanov-vk@rudn.ru
ORCID iD: 0000-0001-8163-9663
SPIN-code: 7266-5340

Senior Lecturer of the Department of Mechanics and Control Processes, Academy of Engineering

6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation

Mariia S. Kondrashina

RUDN University

Author for correspondence.
Email: 1132236536@rudn.ru
ORCID iD: 0009-0008-8526-9143

Graduate student of the Department of Mechanics and Control Processes, Academy of Engineering

6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation

Shamil M. Gadzhiev

RUDN University

Email: 1132236511@rudn.ru
ORCID iD: 0009-0006-1570-4133

Graduate student of the Department of Mechanics and Control Processes, Academy of Engineering

6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation

References

  1. Novoselova IY. Socio-ecological-economic selection of the oil pipeline route. Regional Environmental Issues. 2024;(5):85-90. (In Russ.) https://doi.org/10.24412/1728-323X-2024-5-85-89 EDN: VZGQNH
  2. Voronin KS, Grigorieva PV, Cherenstov DA. Methods for estimating the pipeline construction cost when choosing its route. Oil and Gas Studies. 2018;(3):87-91. (In Russ.) https://doi.org/10.31660/0445-0108-2018-3-87-91 EDN: XTHSLR
  3. Arya AK, Jain R, Yadav S, Bisht S, Gautam S. Recent trends in gas pipeline optimization. Materials Today: Proceedings. 2022;57(4):1455-1461. https://doi.org/10.1016/j.matpr.2021.11.232
  4. Bozdağ A, Yavuz F, Günay AS. AHP and GIS based land suitability analysis for Cihanbeyli (Turkey) county. Environmental Earth Sciences. 2016;75(9):1-15. https://doi.org/10.1007/s12665-016-5558-9 EDN: OCVRFR
  5. Gyabeng BA. Selection of optimum petroleum pipeline routes using a multi-criteria decision analysis and GIS least-cost path approach. International Journal of Scientific and Research Publications (IJSRP). 2022;10(6):572-579. http://doi.org/10.29322/IJSRP.10.06.2020.p10270
  6. Durmaz Aİ, Ünal EÖ, Aydın CC. Automatic pipeline route design with multi-criteria evaluation based on least-cost path analysis and line-based cartographic simpli-fication: A case study of the Mus project in Turkey. ISPRS International Journal of Geo-Information. 2019;8(4):173. https://doi.org/10.3390/ijgi8040173
  7. Nirala PK, Kumar M, Singh P, Singh P, Das B. Route alignment selection and planning for Ganga Express Way from Meerut to Prayagraj region based on multi-criteria decision analysis techniques with geographic information systems and remote sensing techniques. Chinese Journal of Urban and Environmental Studies. 2025;13(2):2550012. https://doi.org/10.1142/S2345748125500125
  8. Hart PE, Nilsson NJ, Raphael BA. A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics. 1968;4(2):100-107. http://doi.org/10.1109/TSSC.1968.300136
  9. Holland JH. Adaptation in natural and artificial systems. MIT Press Publ.; 1992. ISBN 0262581116, 9780262581110
  10. Naaman DW, Ahmed BT, Ibrahim IM. Optimiza-tion by Nature: A Review of Genetic Algorithm Techniques. The Indonesian Journal of Computer Science (IJCS). 2025;14(1):268-284. https://doi.org/10.33022/ijcs.v14i1.4596

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