优化木材供应链:以滨海边疆区为例的数学模型和地区来源分析

R. S. Rogulin
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引用次数: 0

摘要

优化原材料供应与木材加工厂出现的问题密切相关。文章考虑了这样一种情况,即林业工厂没有自己的原材料来源(如伐木者),在规划的最后阶段,根据以前的交易数据寻求最佳解决方案。本文提出了一个数学模型,可以估算出整个规划期内利润值的最优路径。该模型的一个显著特点是,它考虑到了原材料运抵仓库后可用于定向刨花板生产的有用量份额,以及在不确定条件下的批量交货时间。在对俄罗斯商品交易所和滨海边疆区一家企业的数据进行测试后,该模型被用于计算各种数据下的最佳利润轨迹,包括原材料量、批量交货时间和其他重要生产指标,如利润额和货物生产量。分析结果表明,在规划供应链和生产量方面存在困难。对作为原材料来源的地区进行了分析,并确定了从哪些地区以及在什么时候值得购买原材料。文章详细讨论了数学模型的缺点和优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimisation of Timber Supply Chains: Mathematical Model and Analysis of Regional Sources Using the Example of Primorsky Region
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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