Application of a Genetic Algorithm for Pipeline Route Design
- Authors: Lobanov V.K.1, Kondrashina M.S.1, Gadzhiev S.M.1
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Affiliations:
- RUDN University
- Issue: Vol 26, No 4 (2025)
- Pages: 472-480
- Section: Articles
- URL: https://journals.rcsi.science/2312-8143/article/view/380996
- DOI: https://doi.org/10.22363/2312-8143-2025-26-4-472-480
- EDN: https://elibrary.ru/DPMIXG
- ID: 380996
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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 FederationMariia 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 FederationShamil 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 FederationReferences
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