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

采购 原材料 原始数据 冶炼 时间范围 计算机科学 环境经济学 运筹学 业务 产业组织 经济 工程类 财务 化学 有机化学 营销 程序设计语言
作者
Yishun Liu,Weiping Liu,Shaochong Lin,Chunhua Yang,Keke Huang,Zuo‐Jun Max Shen
出处
期刊:IEEE Transactions on Automation Science and Engineering [Institute of Electrical and Electronics Engineers]
卷期号:21 (4): 5852-5865 被引量:6
标识
DOI:10.1109/tase.2023.3319390
摘要

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. Note to Practitioners —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.

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