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  • Исследование возможности применения генетических алгоритмов к решению задач планирования работы электроподвижного состава метрополитена
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Subject
News
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.

 

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Исследование возможности применения генетических алгоритмов к решению задач планирования работы электроподвижного состава метрополитена

Электроника и электрооборудование транспорта. 2017. № 6. С. 37–40.
Чжо М. А., Sidorenko V.

This paper is a part of continuation publications on the topic of genetic algorithms application to the scheduling of underground rolling stock maintenance. The authors implemented the adaptive crossover selection algorithms within the genetic algorithm framework according to the features of the scheduling problem. Then the authors investigated the possibilities of genetic algorithm by using the different crossover types in solving rolling stock scheduling problem, and the influence of parameters in genetic algorithm on the results obtained. The results of genetic algorithm application are described.

Research target: Computer Science Economics and Management Construction Mechanics and Mechanical Engineering Effective Natural Resource Management
Priority areas: management IT and mathematics business informatics engineering science
Language: Russian
Full text
Keywords: оптимизацияoptimizationтехническое обслуживаниепланированиеschedulingгенетический алгоритмgenetic algorithmelectrical rolling stockэлектроподвижной составtechnical maintenance
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