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Handbook on Data Envelopment Analysis pp 211–240Cite as

Chance-Constrained DEA

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 164))

Abstract

Incorporation of random variations into DEA analysis has received significant attention in recent years. This chapter describes some of these developments and offers examples of possible uses in the area of chance-constrained programming models in DEA.

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Author information

Authors and Affiliations

  1. Red McCombs School of Business, University of Texas at Austin, Austin, TX, 78712, USA

    William W. Cooper

  2. School of Business, Adelphi University, Garden City, NY, 11530, USA

    Zhimin Huang & Susan X. Li

Authors
  1. William W. Cooper
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  2. Zhimin Huang
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  3. Susan X. Li
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Corresponding author

Correspondence to Zhimin Huang .

Editor information

Editors and Affiliations

  1. McCombs School of Business, Dept. Management Science &, University of Texas, Austin, University Station 1, Austin, 78712-0212, Texas, USA

    William W. Cooper

  2. Dept. Industrial and, Operations Engineering, University of Michigan, Beal Avenue 1205, Ann Arbor, 48109-2117, Michigan, USA

    Lawrence M. Seiford

  3. Dept. Management, Worcester Polytechnic Institute, Institute Road 100, Worcester, 01609, Massachusetts, USA

    Joe Zhu

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Cooper, W.W., Huang, Z., Li, S.X. (2011). Chance-Constrained DEA. In: Cooper, W., Seiford, L., Zhu, J. (eds) Handbook on Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 164. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-6151-8_9

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