Two-Stage Production Planning Under Stochastic Demand: Case Study of Fertilizer Manufacturing

IF 2 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Chia-Nan Wang, Shao-Dong Syu, C. Chou, Viet Tinh Nguyen, Dang Van Thuy Cuc
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引用次数: 0

Abstract

: Agriculture is a key facilitator of economic prosperity and nourishes the huge global population. To achieve sustainable agriculture, several factors should be considered, such as increasing nutrient and water efficiency and/or improving soil health and quality. Using fertilizer is one of the fastest and easiest ways to improve the quality of nutrients inland and increase the effec-tiveness of crop yields. Fertilizer supplies most of the necessary nutrients for plants, and it is estimated that at least 30%–50% of crop yields is attributable to commercial fertilizer nutrient inputs. Fertilizer is always a major concern in achieving sustainable and efficient agriculture. Applying reasonable and cus-tomized fertilizers will require a significant increase in the number of formulae, involving increasing costs and the accurate forecasting of the right time to apply the suitable formulae. An alternative solution is given by two-stage production planning under stochastic demand, which divides a planning schedule into two stages. The primary stage has non-existing demand information, the inputs of which are the proportion of raw materials needed for producing fertilizer products, the cost for purchasing pays attention to maximizing total profit based on information from customer demand, as well as being informed regarding concerns about system cost at Stage 2.
随机需求下的两阶段生产计划:以化肥制造业为例
当前位置农业是经济繁荣的重要推动者,养活着全球庞大的人口。为实现可持续农业,应考虑几个因素,例如提高养分和水的效率和/或改善土壤健康和质量。使用肥料是改善内陆养分质量和提高作物产量效率的最快和最简单的方法之一。肥料为植物提供大部分必需的养分,据估计,至少30%-50%的作物产量可归因于商业肥料养分投入。肥料一直是实现可持续和高效农业的主要关注点。施用合理和定制的肥料将需要大幅度增加配方的数量,包括增加成本和准确预测使用合适配方的正确时间。给出了随机需求下的两阶段生产计划的一种替代方案,该方案将生产计划分成两个阶段。初级阶段有不存在的需求信息,其输入是生产肥料产品所需原材料的比例,采购成本关注的是基于客户需求信息的总利润最大化,以及阶段2对系统成本的关注。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cmc-computers Materials & Continua
Cmc-computers Materials & Continua 工程技术-材料科学:综合
CiteScore
5.30
自引率
19.40%
发文量
345
审稿时长
1 months
期刊介绍: This journal publishes original research papers in the areas of computer networks, artificial intelligence, big data management, software engineering, multimedia, cyber security, internet of things, materials genome, integrated materials science, data analysis, modeling, and engineering of designing and manufacturing of modern functional and multifunctional materials. Novel high performance computing methods, big data analysis, and artificial intelligence that advance material technologies are especially welcome.
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