Developing a new chance-constrained data envelopment analysis in the presence of stochastic data
by Ehsan Momeni; Reza Farzipoor Saen
International Journal of Business Excellence (IJBEX), Vol. 5, No. 3, 2012

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.

Online publication date: Thu, 31-Jul-2014

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