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Designing a Russian–Chinese Omnichannel Logistics Network for the Supply of Bioethanol

Year: 2025
Type: article
Abstract: This research considers an AI-driven omnichannel logistics network for bioethanol supply from Russia to China. The proposed model integrates information, transportation, and financial flows into a unified simulation framework designed to support flexible and sustainable cross-border logistics. Using a combination of machine learning, multi-objective evaluation, and reinforcement learning, the system models and ranks alternative transportation routes under varying operational conditions. Results indicate that a mixed corridor through Kazakhstan and Kyrgyzstan offers the best balance of cost, time, emissions, and customs reliability. The findings highlight the potential of AI-enhanced logistics systems in supporting low-carbon energy trade and cross-border infrastructure coordination.
DOI: 10.3390/su17177968
Authors: Sergey Barykin, Wenye Zhang, Daria Dinets, Andrey Nechesov, Nikolay Didenko, Djamilia Skripnuk, Olga Kalinina, Tatiana Kharlamova, Andrey Kharlamov, Anna Teslya, Gumar Batov, Evgenii Makarenko
Institutions: Peter the Great St. Petersburg Polytechnic University, Peoples' Friendship University of Russia, Saint Petersburg State University of Economics, Russian Academy of Sciences, Kabardino-Balkarian Scientific Center, Saint Petersburg State University of Aerospace and Instrumentation
Language: English
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4413992202
FWCI: 1.55
Cites: 26
Cited by: 3
Related to: 10