基于改进GM(1,1)的洪涝灾害应急物资动态需求预测

doi:10.16182/j.issn1004731x.joss.17-0112

系统仿真学报 ›› 2019, Vol. 31 ›› Issue (4): 702-709.doi: 10.16182/j.issn1004731x.joss.17-0112

基于改进GM(1,1)的洪涝灾害应急物资动态需求预测

胡忠君¹, 刘艳秋¹, 李佳²

1.沈阳工业大学管理学院,辽宁沈阳 110870;
2.沈阳工业大学信息科学与工程学院,辽宁沈阳 110870

收稿日期:2017-03-16 修回日期:2017-06-14 出版日期:2019-04-08 发布日期:2019-11-20
作者简介:胡忠君(1970-),男,辽宁沈阳,博士,工程师,研究方向为物流系统管理与工程;刘艳秋(1963-),男,吉林四平,博士生,教授,博导,研究方向为物流系统可靠性等。
基金资助:
国家自然科学基金(70431003)

Dynamic Demand Forecast of Emergency Materials for Flood Disasters Based on Improved GM (1,1) Model

Hu Zhongjun¹, Liu Yanqiu¹, Li Jia²

1. School of Management, Shenyang University of Technology, Shenyang 110870, China;
2. School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870, China

Received:2017-03-16 Revised:2017-06-14 Online:2019-04-08 Published:2019-11-20

摘要/Abstract

摘要： 洪涝灾害的突发性及不确定性使得灾害发生后,难以搜集到大样本数据对应急物资的需求量进行快速准确的预测。以灰色系统理论为基础,提出一种改进GM(1,1)动态预测模型,结合库存管理方法构建应急物资动态需求模型,以湖南省2016年3月发生的洪涝灾害为真实案例,对此文提出的模型有效性进行验证。结果表明：改进GM(1,1)模型具有可行性与实用性,比传统GM(1,1)模型具有更高的预测精度。

关键词: 改进GM(1,1)模型, 洪涝灾害, 动态预测, 库存管理

Abstract: The sudden and uncertainties of the flood disaster make it difficult to collect large sample data for forecasting the demand of emergency materials quickly and accurately. Based on this, this paper proposes an improved GM (1,1) dynamic forecasting model based on the gray system theory; constructs the dynamic demand model of emergency materials in combination with the inventory management method; and takes the real flood disaster in March 2016 as a case study. The validity of the model proposed in this paper is verified. The results show that the improved GM (1,1) model is feasible and practicable, and has higher prediction accuracy than the traditional GM (1,1) model.

Key words: improved GM (1,1) model, flood disaster, dynamic forecasting, inventory management

中图分类号:

F252

胡忠君, 刘艳秋, 李佳. 基于改进GM(1,1)的洪涝灾害应急物资动态需求预测[J]. 系统仿真学报, 2019, 31(4): 702-709.

Hu Zhongjun, Liu Yanqiu, Li Jia. Dynamic Demand Forecast of Emergency Materials for Flood Disasters Based on Improved GM (1,1) Model[J]. Journal of System Simulation, 2019, 31(4): 702-709.

参考文献

[1] Ozdamar L, Ekinci E, Kucukyazici B.Emergency logistics planning in natural disasters[J]. Annals of Operations Research (S0254-5330), 2004, 129(1): 217-245.
[2] 曾波, 刘思峰, 方志耕, 等. 灰色组合预测模型及应用[J]. 中国管理科学, 2009, 17(5): 150-155.
Zeng Bo, Liu Sifeng, Fang Zhigeng, et al.Grey Combined Forecast Models and Its Application[J]. Chinese Journal of Management Science, 2009, 17(5): 150-155.
[3] Timofeeva G A, Timofeev N A.Forecasting credit portfolio components with a Markov chain model[J]. Automation and Remote Control (S0005-1179), 2012, 73(4): 637-651.
[4] Liu Sifeng, Liu Yi.Grey systems theory and applications[M]. Berlin Heidelberg: Springer-Verlab, 2010: 107-148.
[5] Nolz C P, Semet F, Doerner F K.Risk approaches for delivering disaster relief supplies[J]. OR Spectrum (S0171-6468), 2011, 33(3): 543-569.
[6] Najafi M, Eshghi K, Dullaert W.A multi-objective robust optimization model for logistics planning in the earthquake response phase[J]. Transportation Research Part E: Logistics and Transportation Review (S1366-5545), 2013, 49(1): 217-249.
[7] Sheu J B.An emergency logistics distribution approach for quick response to urgent relief demand in disasters[J]. Transportation Research Part E: Logistics and Transportation Review (S1366-5545), 2007, 43(6): 687-709.
[8] Chang F S, Wu J S, Lee C N, et al.Greedy-search-based multi-objective genetic algorithm for emergency logistics scheduling[J]. Expert Systems with Applications (S0957-4174), 2014, 41(6): 2947-2956.
[9] 陈方超, 管俊阳, 王道重, 等. 突发事件应急救援物资需求预测的方法研究[J]. 交通信息与安全, 2014, 32(4): 155-159.
Chen Fangchao, Guan Junyang, Wang Daochong, et al.Method for Emergency Materials Demand Forecasting in Sudden Events[J]. Journal of Transport Information and Safety, 2014, 32(4): 155-159.
[10] 傅志妍, 陈坚. 灾害应急物资需求预测模型研究[J]. 物流科技, 2009, 32(10): 11-13.
Fu Zhiyan, Chen Jian.Reaearch on Emegency Material Demand Forecast Model in Disaster[J]. Logistics Sci-Tech, 2009, 32(10): 11-13.
[11] 曾波, 孟伟, 刘思峰, 等. 面向灾害应急物资需求的灰色异构数据预测建模方法[J]. 中国管理科学, 2015, 23(8): 84-91.
Zeng Bo, Meng Wei, Liu Sifeng, et al.Predictioon Modeling Method of Grey Isomerism Data for Calamity Emergency Material Demand[J]. Chinese Journal of Management Science, 2015, 23(8): 84-91.
[12] 邓聚龙. 灰色系统基本方法[M]. 武汉: 华中科技大学出版社, 2005: 56-68.
Deng Julong.Grey system basic method[M]. Wuhan: Huazhong university of science and technology press, 2005: 56-68.
[13] 王子赟, 纪志成. 基于GM(2,1)和辨识算法的风电功率短期预测研究[J]. 系统仿真学报, 2015, 27(11): 2762-2777.
Wang Ziyun, Ji Zhicheng.GM(2,1) Model and Identification Algorithm Based Wind Power Generation Short-term Prediction[J]. Journal of System Simulation, 2015, 27(11): 2762-2777.
[14] 湖南省防汛抗旱网[DB/OL]. http://222.240.128.250: 8080/Management/GovernmentAffairs, 2016.
Hunan province flood control and drought relief network [DB/OL]. http:// 222. 240. 128. 250: 8080/ Management /GovernmentAffairs, 2016.

基于改进GM(1,1)的洪涝灾害应急物资动态需求预测

Dynamic Demand Forecast of Emergency Materials for Flood Disasters Based on Improved GM (1,1) Model

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