基于改进TOPSIS-DEA模型的采油厂绩效评估方法
Performance Evaluation Method for Oil Production Plant Base on Improved TOPSIS-DEA Model
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- 引用格式:
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刘岩,罗东坤,魏新强,张宝生.基于改进TOPSIS-DEA模型的采油厂绩效评估方法[J].天然气与石油,2015,33(4):0.doi:
Liu Yan, Luo Dongkun, Wei Xinqiang ,Zhang Baosheng.Performance Evaluation Method for Oil Production Plant Base on Improved TOPSIS-DEA Model[J].Natural Gas and Oil,2015,33(4):0.doi:
- DOI:
- 作者:
- 刘 岩1 罗东坤1 魏新强2 张宝生1
Liu Yan, Luo Dongkun, Wei Xinqiang ,Zhang Baosheng
- 作者单位:
- 1.中国石油大学(北京)工商管理学院,2.中国石油集团经济技术研究院
1.China University of Petroleum (Beijing) Institute of Business Administration;2.China Petroleum Group Economic and Technical Institute
- 关键词:
- 绩效评估；数据包络分析；理想点排序；偏好矩阵
Performance evaluation; DEA; TOPSIS; Preference matrix
- 摘要:
- 传统的数据包络分析(DEA)方法应用于绩效评估无法体现决策者的决策偏好,也无法对有效评价单元进行全排序。在考虑偏好的前提下,运用主观评价方法构造DEA偏好矩阵；以理想点排序(TOPSIS)原理为基础,通过虚拟最优和最差前沿面的方式构造正理想点和负理想点,并以相对贴近度指数计算各评价单元的DEA全排序值。采用12家采油厂的数据进行实例分析,分别以油气生产、安全生产和环保生产为优先条件进行绩效评估,结果显示改进TOPSIS-DEA模型方法在采油厂绩效评估优选中有实用意义。
As a traditional performance evaluation method, DEA does not embody decision preference as well as construct a total ordering of effective evaluation units. Under the premise of considering the preference of decision makers, built is a DEA preference matrix through using subjective evaluation methods. Based on the principle of TOPSIS sequencing, built are positive ideal points and negative ideal points by creating the virtual best and the virtual worst frontier. According to these results, the DEA sequencing value of each evaluation unit is determined via the relative closeness degree. An empirical study is done with the data of 12 oil production plants and conducted is their performance evaluation at various priority conditions such as oil and gas production, safety production, and environmental protection production. Results show that the improved method has practical application value in oil production plant performance evaluation optimization.
