Indian Journal of Science and Technology

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Evaluation of Benchmark Information with Least-distance Measurement Model for Non-convex Frontiers and Petri Net


Affiliations
1 Young Researchers club, Nowshahr Branch, Islamic Azad University, Nowshahr, Iran, Islamic Republic of
2 Department of Mathematics, Islamic Azad University, Qaemshahr Branch, Qaemshahr, Iran, Islamic Republic of
 

Data Envelopment Analysis (DEA) is efficient analysis for similar decision making units (DMUs). It provides a ranking of DMUs relative to each other. DAE in addition to determining efficiency level, provides situations for removing inefficiency by using evaluated benchmark information. The Least-Distance Measurement model is proposed in order to shifting inefficiency to the nearest efficient unit which may not applied in real-world problems about convex technology (i.e., the convexity of the production probability function); thus, expanding DEA to non-convexity technology would be improved the potential of applying the Least-Distance Measurement model. This paper proposes extension of Least-Distance Measurement model in non-convexity technology and we will explore Petri Nets for modeling a leastdistance measurement in non-convex space.

Keywords

Data Envelopment Analysis, Least Distance, FDH, Benchmarking
User

  • Baek C and Lee J (2009) The relevance of DEA benchmarking information and the least-distance measure. 49, 265-275.

  • Charnes A Cooper WW and Rhodes E (1978) Measuring the efficiency of decision making units. 2, 429- 444.

  • Deprins D Simar L and Tulkens H (1984) Measuring labor inefficiency in post offices, M. Marchand, P. Pestieau, H. Tulkens (Eds.), The Performance of Public Enterprises: Concepts and Measurement, North-Holland, Amsterdam,pp 243-267.

  • Jeong S and Simar L (2006) Linearly interpolated FDH efficiency score for non convex frontiers 97, 2141-2161.

  • Murata T (1989) Petri Nets: properties, analysis and applications. . 77, 541-580.

  • Raty T (2002) Efficient facet based efficiency index: A variable returns to scale specification. 17, 65-82.

  • Soleimani-damaneh M and Mostefaee A (2009) Stability of the classification of returns to scale in FDH models. 196, 1223-1228.

  • Sueyoshi T and Sekitani K (2007) Computational strategy for Russell measure in DEA: Second-order cone programming. 180, 459- 471.

  • Tulkens H (1993) On FDH efficiency analysis: Some methodological issues and applications to retail banking, courts, and urban transit. . 4, 183-210.

  • Zou M and Zurawski R (1995) Introduction to Petri Nets in flexible and agile automation. Kluwer Acad. Publ. 1-42.


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  • Evaluation of Benchmark Information with Least-distance Measurement Model for Non-convex Frontiers and Petri Net

Abstract Views: 338  |  PDF Views: 96

Authors

Behnam Barzegar
Young Researchers club, Nowshahr Branch, Islamic Azad University, Nowshahr, Iran, Islamic Republic of
Reza Shahverdi
Department of Mathematics, Islamic Azad University, Qaemshahr Branch, Qaemshahr, Iran, Islamic Republic of

Abstract


Data Envelopment Analysis (DEA) is efficient analysis for similar decision making units (DMUs). It provides a ranking of DMUs relative to each other. DAE in addition to determining efficiency level, provides situations for removing inefficiency by using evaluated benchmark information. The Least-Distance Measurement model is proposed in order to shifting inefficiency to the nearest efficient unit which may not applied in real-world problems about convex technology (i.e., the convexity of the production probability function); thus, expanding DEA to non-convexity technology would be improved the potential of applying the Least-Distance Measurement model. This paper proposes extension of Least-Distance Measurement model in non-convexity technology and we will explore Petri Nets for modeling a leastdistance measurement in non-convex space.

Keywords


Data Envelopment Analysis, Least Distance, FDH, Benchmarking

References





DOI: https://doi.org/10.17485/ijst%2F2011%2Fv4i9%2F30234