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Article: Data-Driven Raw Material Robust Procurement for Non-Ferrous Metal Smelter Under Price and Demand Uncertainties

TitleData-Driven Raw Material Robust Procurement for Non-Ferrous Metal Smelter Under Price and Demand Uncertainties
Authors
KeywordsAdaptation models
Costs
data-driven
Metals
Procurement
Production
Raw material procurement
Raw materials
robust optimization
uncertainties
Uncertainty
Issue Date1-Jul-2023
PublisherInstitute of Electrical and Electronics Engineers
Citation
IEEE Transactions on Automation Science and Engineering, 2023, p. 1-14 How to Cite?
Abstract

Non-ferrous metals, as important basic raw materials, are the strategic supports for national economic development. For non-ferrous metal smelting enterprises, raw material procurement is the focal and most important session. Due to the fluctuation of production volumes and the future changes in raw-material prices, the procurement cost of raw materials is high and with a high risk of shortage. In this paper, we propose a multi-period rolling robust procurement model considering price and demand uncertainties. In particular, we design a data-driven method to construct the budget-based uncertainty sets and derive the robust counterpart of the robust procurement model. Comparative experiments on the real data with classic and advanced procurement policies show that our proposed solution approach achieves the lowest cost under the premise of continuous supply of raw materials. Interestingly, we observe that limited capital and warehouse capacity can effectively restrain unreasonable behavior and thus not to cause big losses in uncertain environments. In addition, a relatively long planning horizon can be counterproductive. These valuable and actionable insights can well guide practical decision-making. —For the raw material procurement of non-ferrous metal smelter, this article proposes a multi-period rolling robust procurement model considering price and demand uncertainties. Taking account of the dynamic characteristics of raw-material prices and the seasonal characteristics of raw-material demands, a data-driven method to construct budget-based uncertainty sets is designed. In particular, we derive the solvable robust counterpart of the robust procurement model. The proposed approach can reduce costs ensuring the continuous supply of raw materials. Some interesting and actionable managerial insights are obtained that can well guide practical decision-making, and the proposed data-driven approach is realizable.


Persistent Identifierhttp://hdl.handle.net/10722/336585
ISSN
2023 Impact Factor: 5.9
2023 SCImago Journal Rankings: 2.144
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiu, Yishun-
dc.contributor.authorLiu, Weiping-
dc.contributor.authorLin, Shaochong-
dc.contributor.authorYang, Chunhua-
dc.contributor.authorHuang, Keke-
dc.contributor.authorShen, Zuo-Jun Max-
dc.date.accessioned2024-02-22T09:52:24Z-
dc.date.available2024-02-22T09:52:24Z-
dc.date.issued2023-07-01-
dc.identifier.citationIEEE Transactions on Automation Science and Engineering, 2023, p. 1-14-
dc.identifier.issn1545-5955-
dc.identifier.urihttp://hdl.handle.net/10722/336585-
dc.description.abstract<p>Non-ferrous metals, as important basic raw materials, are the strategic supports for national economic development. For non-ferrous metal smelting enterprises, raw material procurement is the focal and most important session. Due to the fluctuation of production volumes and the future changes in raw-material prices, the procurement cost of raw materials is high and with a high risk of shortage. In this paper, we propose a multi-period rolling robust procurement model considering price and demand uncertainties. In particular, we design a data-driven method to construct the budget-based uncertainty sets and derive the robust counterpart of the robust procurement model. Comparative experiments on the real data with classic and advanced procurement policies show that our proposed solution approach achieves the lowest cost under the premise of continuous supply of raw materials. Interestingly, we observe that limited capital and warehouse capacity can effectively restrain unreasonable behavior and thus not to cause big losses in uncertain environments. In addition, a relatively long planning horizon can be counterproductive. These valuable and actionable insights can well guide practical decision-making. —For the raw material procurement of non-ferrous metal smelter, this article proposes a multi-period rolling robust procurement model considering price and demand uncertainties. Taking account of the dynamic characteristics of raw-material prices and the seasonal characteristics of raw-material demands, a data-driven method to construct budget-based uncertainty sets is designed. In particular, we derive the solvable robust counterpart of the robust procurement model. The proposed approach can reduce costs ensuring the continuous supply of raw materials. Some interesting and actionable managerial insights are obtained that can well guide practical decision-making, and the proposed data-driven approach is realizable.<br></p>-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers-
dc.relation.ispartofIEEE Transactions on Automation Science and Engineering-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectAdaptation models-
dc.subjectCosts-
dc.subjectdata-driven-
dc.subjectMetals-
dc.subjectProcurement-
dc.subjectProduction-
dc.subjectRaw material procurement-
dc.subjectRaw materials-
dc.subjectrobust optimization-
dc.subjectuncertainties-
dc.subjectUncertainty-
dc.titleData-Driven Raw Material Robust Procurement for Non-Ferrous Metal Smelter Under Price and Demand Uncertainties-
dc.typeArticle-
dc.identifier.doi10.1109/TASE.2023.3319390-
dc.identifier.scopuseid_2-s2.0-85177059902-
dc.identifier.spage1-
dc.identifier.epage14-
dc.identifier.eissn1558-3783-
dc.identifier.isiWOS:001115883700001-
dc.identifier.issnl1545-5955-

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