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A Multiple Objective Programming Approach To Data Envelopment Analysis

In: New Frontiers Of Decision Making For The Information Technology Era

Author

Listed:
  • C. I. CHIANG

    (Institute of Traffic and Transportation, National Chiao Tung University, 114, 4F, Sec. 1, Chung Hsiao W. Rd., Taipei, Taiwan)

  • G. H. TZENG

    (College of Management, National Chiao Tung University, 1001, Ta-Hsueh Rd., Hsinchu 300, Taiwan)

Abstract

In this paper a multiple objectives programming method is applied to improve the discriminating power of classical Data Envelopment Analysis (DEA) method. Unlike the classical DEA model often producing many relatively efficient decision making units (DMUs), this new approach enjoys more discriminating power, which results in less DMUs with efficiency ratio as 1. In this approach, every DMU's efficiency evaluation is viewed as one objective function to be maximized. A set of common multipliers, input and output weights, can be located not difficultly by using the fuzzy multiple objectives programming approach. In comparison to the number of programming works being same as the number of the DMUs in traditional DEA model, the new approach just needs to solving multiple objectives programming problem once no matter how many DMUs are. Apparently, the new approach is comparatively suitable to solve a problem with a large number of DMUs.

Suggested Citation

  • C. I. Chiang & G. H. Tzeng, 2000. "A Multiple Objective Programming Approach To Data Envelopment Analysis," World Scientific Book Chapters, in: Yong Shi & Milan Zeleny (ed.), New Frontiers Of Decision Making For The Information Technology Era, chapter 15, pages 270-285, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812792907_0015
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    Cited by:

    1. I. Contreras & S. Lozano & M. A. Hinojosa, 2021. "A bargaining approach to determine common weights in DEA," Operational Research, Springer, vol. 21(3), pages 2181-2201, September.
    2. Tsai, Hsiang-Chih & Chen, Chun-Mei & Tzeng, Gwo-Hshiung, 2006. "The comparative productivity efficiency for global telecoms," International Journal of Production Economics, Elsevier, vol. 103(2), pages 509-526, October.

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