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Developing a new chance-constrained data envelopment analysis in the presence of stochastic data

Author

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  • Ehsan Momeni
  • Reza Farzipoor Saen

Abstract

Outsourcing in logistics is a very significant theme and third-party reverse logistics (3PL) provider evaluation and selection has to be realised in a careful manner in order to provide the expected benefits. Data envelopment analysis (DEA) has been successfully used to select the most efficient supplier(s) in a supply chain. In this study, a new Russell chance-constrained data envelopment analysis (RCCDEA) approach is proposed to assist the decision-makers to determine the most appropriate 3PL providers in the presence of multiple performance measures that are uncertain. Because of the complexity of the proposed model, a genetic algorithm is presented as a solution procedure to obtain near to optimum solutions. The usefulness of the proposed model and algorithm was validated by its application to an illustrative example.

Suggested Citation

  • Ehsan Momeni & Reza Farzipoor Saen, 2012. "Developing a new chance-constrained data envelopment analysis in the presence of stochastic data," International Journal of Business Excellence, Inderscience Enterprises Ltd, vol. 5(3), pages 169-194.
    • Handle: RePEc:ids:ijbexc:v:5:y:2012:i:3:p:169-194
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