Annals of Operations Research

, Volume 66, Issue 4, pp 279–295 | Cite as

Chapter 13 Satisficing DEA models under chance constraints

  • W. W. Cooper
  • Zhimin Huang
  • Susan X. Li
Part IV Statistical And Stochastic Characterizations


DEA (Data Envelopment Analysis) models and concepts are formulated here in terms of the “P-Models” of Chance Constrained Programming, which are then modified to contact the “satisficing concepts” of H.A. Simon. Satisficing is thereby added as a third category to the efficiency/inefficiency dichotomies that have heretofore prevailed in DEA. Formulations include cases in which inputs and outputs are stochastic, as well as cases in which only the outputs are stochastic. Attention is also devoted to situations in which variations in inputs and outputs are related through a common random variable. Extensions include new developments in goal programming with deterministic equivalents for the corresponding satisficing models under chance constraints.


Efficiency satisficing data envelopment analysis stochastic efficiency 


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Copyright information

© J.C. Baltzer AG, Science Publishers 1996

Authors and Affiliations

  • W. W. Cooper
    • 1
  • Zhimin Huang
    • 2
  • Susan X. Li
    • 2
  1. 1.Graduate School of BusinessThe University of Texas at AustinAustinUSA
  2. 2.Schools of Business and BankingAdelphi University, Garden CityLong IslandUSA

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