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Optimization of naphtha purchase price using a price prediction model

机译:使用价格预测模型优化石脑油购买价格

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摘要

In order to meet company needs, various models of naphtha price forecasting and optimization models of average naphtha purchase price have been developed. However, these general models are limited in their ability to predict future trends as they only include quantitative data. Furthermore, naphtha price predictions based on fluctuation trends have not been published in the literature. Thus, we developed a system dynamics (SD) model considering time-series data, mathematical formulations, and qualitative factors. The results obtained from our model were compared with the published literature. The best result of the SD is the European naphtha forecasting price model, and the forecasting accuracy percentage shows 92.82%. Furthermore, a nonlinear programming (NLP) model was developed to optimize the purchase price by considering the naphtha price of the forecasting models. In addition, the average optimization value was approximately 45.07 USD/ton cheaper than that of the heuristic approach.
机译:为了满足公司需求,已经开发了各种石脑油价格预测模型和平均石脑油购买价格优化模型。但是,由于这些通用模型仅包含定量数据,因此它们预测未来趋势的能力有限。此外,基于波动趋势的石脑油价格预测尚未在文献中发表。因此,我们考虑了时间序列数据,数学公式和定性因素,开发了系统动力学(SD)模型。从我们的模型获得的结果与已发表的文献进行了比较。 SD的最佳结果是欧洲石脑油预测价格模型,预测准确性百分比为92.82%。此外,开发了一个非线性规划(NLP)模型,通过考虑预测模型的石脑油价格来优化购买价格。此外,平均优化值比启发式方法便宜约45.07美元/吨。

著录项

  • 来源
    《Computers & Chemical Engineering》 |2016年第4期|226-236|共11页
  • 作者单位

    Department of Chemical and Biomolecular Engineering, Yonsei University, 50 Yonsei ro, Seodaemun-ku, Seoul 120-749, South Korea;

    Department of Chemical and Biomolecular Engineering, Yonsei University, 50 Yonsei ro, Seodaemun-ku, Seoul 120-749, South Korea;

    Department of Chemical and Biomolecular Engineering, Yonsei University, 50 Yonsei ro, Seodaemun-ku, Seoul 120-749, South Korea;

    Hanwha Total Corporation, 411, Dokgot-ri, Daesan-eup Seosan-si, Chungcheongnam-do 356-711, South Korea;

    Engineering Development Research Center (EDRC), Seoul National University, 1, Gwanak-ro, Gwanak-gu, Seoul 151-744, South Korea;

    Department of Chemical and Biomolecular Engineering, Yonsei University, 50 Yonsei ro, Seodaemun-ku, Seoul 120-749, South Korea;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Purchase price optimization; Artificial neural network; Forecasting model; System dynamics; Heuristics;

    机译:采购价格优化;人工神经网络;预测模型;系统动力学;启发式;

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