Barabási–Albert-Based Network Growth Model to Sustainable Urban Planning

Aleksandr Abramov, Uliana Gorik, Andrei Velichko, Vladimir Nelyub, Aleksandr Samoshkin, Andrei Gantimurov, Aleksei Borodulin, Vadim S. Tynchenko () and Ivan Malashin ()
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Aleksandr Abramov: Scientific Department, Far Eastern Federal University, 690922 Vladivostok, Russia
Uliana Gorik: Scientific Department, Far Eastern Federal University, 690922 Vladivostok, Russia
Andrei Velichko: Scientific Department, Far Eastern Federal University, 690922 Vladivostok, Russia
Vladimir Nelyub: Scientific Department, Far Eastern Federal University, 690922 Vladivostok, Russia
Aleksandr Samoshkin: Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia
Andrei Gantimurov: Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia
Aleksei Borodulin: Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia
Vadim S. Tynchenko: Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia
Ivan Malashin: Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia

Sustainability, 2025, vol. 17, issue 3, 1-24

Abstract: Urban planning and development require methodologies to address the challenges of managing urban growth. This study uses Vladivostok as a case study to explore urban evolution and apply predictive models for socio-economic development. By analyzing the life cycle of the city and breaking down its growth processes into key components, specific patterns and strategies tailored to Vladivostok’s development are identified. The Barabási–Albert (BA) network growth model is used to study the temporal dynamics of the city’s urban network, enabling forecasts and optimization of its infrastructure, communication systems, and social environment. The approach shown in this study can be adapted to other cities, providing a framework for analyzing urban changes and supporting the development of strategies for sustainable growth and urban management.

Keywords: urban development; network growth models; socio-economic forecasting; urban evolution (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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