Production Inventory Optimization Considering Direct and Indirect Carbon Emissions under a Cap-and-Trade Regulation

IF 3.6 Q2 MANAGEMENT
Y. Daryanto, Djoko Setyanto
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引用次数: 0

Abstract

Background: The latest global agreement on net-zero emissions encourages new studies on production inventory optimization that promote carbon emissions reduction without harming a company’s profit performance, particularly because certain carbon-pricing regulations bind manufacturing companies. Methods: This study aims to develop a production inventory model that considers direct and indirect emissions in three emission scopes. It incorporates emissions from production, material handling, transportation, and waste disposal for further treatment under a carbon cap-and-trade regulation. With the help of Maple software, a convex total cost function was solved. Results: The results show that the optimum production quantity depends on the values of demand, setup cost, holding cost, fixed cost per delivery, fixed cost for waste disposal, and other parameters related to carbon prices. This study also found that the total cost was highly dependent on the values of the carbon cap, carbon price, and delivery distance. Meanwhile, changes in the delivery distance and fuel emissions standard significantly impacted total emissions. Conclusions: The proposed model can guide manufacturing companies in setting the optimum production quantity per cycle. Moreover, they must carefully manage the delivery and setting of the carbon cap and carbon price from the government.
限额与交易下考虑直接和间接碳排放的生产库存优化
背景:最新的全球净零排放协议鼓励对生产库存优化进行新的研究,在不损害公司利润表现的情况下促进碳减排,特别是因为某些碳定价法规约束了制造公司。方法:本研究旨在建立一个生产清单模型,在三个排放范围内考虑直接和间接排放。它将生产、材料处理、运输和废物处理的排放纳入碳排放总量管制和交易条例的进一步处理。在Maple软件的帮助下,求解了一个凸的总成本函数。结果:结果表明,最佳生产量取决于需求值、设置成本、持有成本、每次交付的固定成本、废物处理的固定成本以及其他与碳价格相关的参数。这项研究还发现,总成本在很大程度上取决于碳上限、碳价格和交付距离的值。同时,运输距离和燃料排放标准的变化对总排放量产生了重大影响。结论:所提出的模型可以指导制造企业设定每个周期的最佳生产量。此外,他们必须谨慎管理政府对碳上限和碳价格的交付和设定。
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
Logistics-Basel
Logistics-Basel Multiple-
CiteScore
6.60
自引率
0.00%
发文量
0
审稿时长
11 weeks
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