Оперативное планирование доставки вакцин
Ларин О.Н.1,2 
, Матосов М.В.1
1 Российский экономический университет им. Г.В. Плеханова, Москва, Россия
2 Российский университет транспорта (МИИТ), Москва, Россия
Статья в журнале
Экономика, предпринимательство и право (РИНЦ, ВАК)
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Том 16, Номер 3 (Март 2026)
Аннотация:
Участники цепочек поставок вакцин планируют взаимодействие, как правило, на основе долгосрочных договоров, предусматривающих поставки лекарственных препаратов с установленной периодичность в заданных объемах с использованием одного или нескольких видов транспорта. Однако в чрезвычайных ситуациях поставщики вакцин вынуждены корректировать действующие планы с учётом потребностей новых получателей. Поэтому логистические компании заинтересованы в использовании передовых решений, позволяющих определять оптимальные варианты доставки вакцин всем получателем в полном объеме в установленные сроки в условиях ограниченного количества логистических ресурсов. Для оперативного планирования доставки вакцин предлагается использовать разработанную математическую модель, которая определяет оптимальные по стоимости варианты доставки от поставщика получателям, а также позволяет определять потребное количество логистических ресурсов, необходимое для полного выполнения заявленных объемов. Разработанная модель также может использоваться в качестве основы для разработки моделей комплексного планирования доставки вакцин от множества поставщиков различным получателям
Ключевые слова: холодовая цепь, способ доставки, логистика вакцин, оперативное планирование
JEL-классификация: L81, M11, D24
Источники:
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Страница обновлена: 23.02.2026 в 13:51:09
Operational planning of vaccine delivery
Larin O.N., Matosov M.V.Journal paper
Journal of Economics, Entrepreneurship and Law
Volume 16, Number 3 (March 2026)
Abstract:
Participants in vaccine supply chains typically plan their interactions based on long-term contracts providing for the delivery of drugs at set intervals in specified volumes using one or more modes of transport. However, in emergency situations, vaccine suppliers are forced to adjust existing plans to accommodate the needs of new recipients. Therefore, logistics companies are interested in using advanced solutions that enable them to determine optimal options for delivering vaccines to all recipients in full, within the specified timeframe, given limited logistics resources. For operational vaccine delivery planning, we propose using a developed mathematical model that determines the most cost-effective delivery options from supplier to recipients and allows for determining the required number of logistics resources required to fully fulfill the stated volumes. The developed model can also be used as a basis for developing integrated planning models for vaccine delivery from multiple suppliers to different recipients
Keywords: cold chain, delivery method, vaccine logistics, operational planning
JEL-classification: L81, M11, D24
References:
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Ashvin Ashok, Michael Brison, Yann LeTallec (2017). Improving cold chain systems: Challenges and solutions Vaccine. 35 (17). 2217-2223. doi: 10.1016/j.vaccine.2016.08.045.
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Kartoglu U.H., Moore K.L., Lloyd J.S. (2020). Logistical challenges for potential SARS-CoV-2 vaccine and a call to research institutions, developers and manufacturers Vaccine. 38 (34). 5393-5395. doi: 10.1016/j.vaccine.2020.06.056.
Larin O. N., Matosov M. V. (2024). Vaccine Logistics: Problems and Prospects for Digitalization. Logostics. (10). 46-52.
Lim J., Norman B.A., Rajgopal J. (2022). Redesign of vaccine distribution networks Intl. Trans. in Op. Res.. (29). 200-225. doi: 10.1111/itor.12758.
Lotty Evertje Duijzer, Willem van Jaarsveld, Rommert Dekker (2018). Literature review: The vaccine supply chain European Journal of Operational Research. 268 (1). 174-192. doi: 10.1016/j.ejor.2018.01.015.
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Tan L.J., Barnett M.A., Eisenberg A., Fox Fields H., Hackell J.M., Léger M.M., Meadows B., Moore K.L., Rehm S.J., Rothholz M.C., Smith C., Talkington K., Wexler D.L. (2014). From refrigerator to arm: Issues in vaccination delivery Vaccine. 32 (21). 2389-2393. doi: 10.1016/j.vaccine.2014.02.045.
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Thomas D., Motomoke E., Crawford J., Defawe O., Makaya A., Ngwato J.W., Bompongo J., Monzembela J., Ailstock G., Bancroft E., Magadzire B., Baabo D., Watson N. (2021). Optimized supply chain model reduces health system costs in DRC Vaccine. 39 (30). 4166-4172. doi: 10.1016/j.vaccine.2021.05.083.
Tina-Marie Assi, Korngamon Rookkapan, Jayant Rajgopal, Vorasith Sornsrivichai, Shawn T. Brown, Joel S. Welling (2012). How influenza vaccination policy may affect vaccine logistics Vaccine. 30 (30). 4517-4523. doi: 10.1016/j.vaccine.2012.04.041.
Ulla K. Griffiths, Viola S. Korczak, Dereje Ayalew, Asnakew Yigzaw (2009). Incremental system costs of introducing combined DTwP–hepatitis B–Hib vaccine into national immunization services in Ethiopia Vaccine. 27 (9). 1426-1432. doi: 10.1016/j.vaccine.2008.12.037.
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Xu Sun, Eugenia Ama Andoh, Hao Yu. (2021). A simulation-based analysis for effective distribution of COVID-19 vaccines: A case study in Norway Transportation Research Interdisciplinary Perspectives. 11 100453. doi: 10.1016/j.trip.2021.100453.
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