mirtrМир транспортаWorld of Transport and Transportation1992-3252Russian University of Transport (RUT)10.30932/1992-3252-2023-21-5-7mirtr-2563Research ArticleУПРАВЛЕНИЕ И ЭКОНОМИКАMANAGEMENT, CONTROL AND ECONOMICSОптимизация лесопромышленных цепочек поставок: математическая модель и анализ региональных источников на примере Приморского краяOptimisation of Timber Supply Chains: Mathematical Model and Analysis of Regional Sources Using the Example of Primorsky RegionРогулинР. С.RogulinR. S.

Рогулин Родион Сергеевич – кандидат экономических наук, доцент кафедры математики и моделирования

 Владивосток

Rogulin, Rodion S., Ph.D. (Economics), Associate Professor at the Department of Mathematics and Modelling

Vladivostok

rafassiaofusa@mail.ruВладивостокский государственный университет экономики и сервисаРоссияVladivostok State University of Economics and ServiceRussian Federation2023170420242156069Copyright © Рогулин Р.С., 20242024Рогулин Р.С.Rogulin R.S.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://mirtr.elpub.ru/jour/article/view/2563

Оптимизация поставок сырья тесно связана с проблемами, возникающими на лесоперерабатывающих предприятиях. Оценка оптимальности решений часто становится актуальным вопросом.

В данной статье рассматривается сценарий работы лесопромышленного предприятия без собственных источников сырья, таких как лесозаготовители, которое стремится найти оптимальное решение на конечном этапе планирования, основываясь на данных о предыдущих сделках. В качестве источника сырья рассматривается товарно-сырьевая биржа, где лоты ежедневно появляются в различных регионах добывающих предприятий в случайном порядке.

Научная литература предлагает множество методов расчёта оптимальной прибыли на протяжении всего планового периода, но эти подходы не учитывают многие важные особенности лесоперерабатывающих предприятий.

В данной работе представлена математическая модель, которая позволяет оценить оптимальный путь для значений прибыли на протяжении всего периода планирования. Отличительной чертой модели является учёт доли полезного объёма сырья, который можно использовать в производстве ОСБ-плит после зачисления на склад, а также учет времени доставки лотов в условиях неопределённости.

После проведения тестирования на данных товарносырьевой биржи России и одного из предприятий Приморского края, модель была применена для расчёта оптимальной траектории прибыли для различных данных, включая объёмы сырья, время доставки лотов и другие важные показатели производства, такие как объём прибыли и объём производства товаров. Анализ результатов выявил сложности в планировании цепочек поставок и объёмов производства. Также проанализированы регионы в качестве источников сырья, определено, из каких регионов и в какой момент стоит закупать сырье. В статье подробно рассмотрены недостатки и преимущества математической модели.

Optimising the supply of raw materials is closely related to the problems that arise at wood processing plants. Assessing the optimality of solutions often becomes a pressing issue.

The article considers the scenario of a forestry plant without its own sources of raw materials, such as loggers, which seeks to find an optimal solution at the final stage of planning, based on data on previous transactions. A commodity exchange is considered as a source of raw materials, where lots appear daily in various regions of logging enterprises in a random order.

The scientific sources offer multiple methods for calculating optimal profit throughout the entire planning period, but these approaches do not consider many important features of forest processing enterprises.

This paper presents a mathematical model that allows estimating the optimal path for profit values throughout the entire planning period. A distinctive feature of the model is that it takes into account the share of the useful volume of raw materials that can be used in production of oriented strand boards after being delivered to the warehouse, as well as the delivery time of lots under conditions of uncertainty.

After testing on data from the Russian Mercantile Exchange and one of Primorsky region enterprises, the model was applied to calculate the optimal profit trajectory for various data, including volumes of raw materials, time of lot delivery and other important production indicators, such as profit volume and volume of goods produced. Analysis of the results revealed difficulties in planning supply chains and production volumes. Regions as sources of raw materials were analysed, and it was determined from which regions and at what point it is worth purchasing raw materials. The article discusses in detail the disadvantages and advantages of the mathematical model.

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The authors declare that there are no conflicts of interest present.