Developing a new chance-constrained data envelopment analysis in the presence of stochastic data. (1st January 2012)

• Record Type: Journal Article
• Authors: Momeni, Ehsan; Farzipoor Saen, Reza
• Is Part Of: International journal of business excellence. Volume 5:Number 3(2012)
• Page Start: 169
• Page End: 194
• Publication Date: 2012-01-01
• Subjects: third-party reverse logistics provider -- 3PL providers selection -- data envelopment analysis -- DEA -- chance-constrained data envelopment analysis -- CCDEA -- genetic algorithm -- GA -- Russell measure -- Russell model; Reengineering (Management) -- Periodicals; Benchmarking (Management) -- Periodicals; Performance -- Management -- Periodicals; 658.401305
• Languages: English
• ISSNs: 1756-0047

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.