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

Ehsan Momeni and Reza Farzipoor Saen

International Journal of Business Excellence, 2012, vol. 5, issue 3, 169-194

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.

Keywords: 3PL; TPL; third-party logistics; reverse logistics providers; provider selection; Malmquist DEA; data envelopment analysis; Robert Russell; efficiency measurement; chance-constrained analysis; genetic algorithms; stochastic data; outsourcing; provider evaluation; expected benefits; efficient suppliers; SCM; supply chain management; decision-making; solution procedures; optimum solutions; business excellence. (search for similar items in EconPapers)
Date: 2012
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