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

Authors: Ehsan Momeni; Reza Farzipoor Saen

Addresses: Department of Industrial Engineering, Islamic Azad University, Firouzkoh Branch, P.O. Box 148, Firouzkoh, Iran. ' Department of Industrial Management, Islamic Azad University, Karaj Branch, P.O. Box 31485-313, Karaj, Iran

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.

DOI: 10.1504/IJBEX.2012.046638

International Journal of Business Excellence, 2012 Vol.5 No.3, pp.169 - 194

Published online: 31 Jul 2014 *

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