A DEA-Benchmarking optimization model and method based on the theory of maximum entropy

  • Authors:

  • Yin-sheng Yang;Ning Li;Hai-cun Liu;Hong-peng Guo

  • Affiliations:

  • School of Biological and Agricultural Engineering, Jilin University, Changchun, P.R. China;School of Biological and Agricultural Engineering, Jilin University, Changchun, P.R. China;School of Biological and Agricultural Engineering, Jilin University, Changchun, P.R. China;School of Biological and Agricultural Engineering, Jilin University, Changchun, P.R. China

  • Venue:
  • ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

Benchmarking is a technique that engages and executes a series of measures to change indexes of the Decision Making Unit (DMU) to excellent by using the gap analysis information between the DMU and benchmark. In this paper, a DEA-Benchmarking model based on the theory of maximum entropy is proposed and the conception of Entropy-DEA efficiency is defined. According to the optimization model based on the theory of maximum entropy, the Entropy-DEA efficient DMUs is regarded as benchmarks, which have more advantages and direction than DEA efficient DMUs. The measure method and existence property of Entropy-DEA efficiency are all analyzed in this paper.