Outsourcing in logistics is a very significant theme and third-party reverse logistics (3PL) provider evaluation and selection has to be realized in a careful manner in order to provide the expected benefits. In this paper a new chance-constrained data envelopment analysis (CCDEA) approach is proposed to assist the decision makers to determine the most appropriate third-party reverse logistics (3PL) providers in the presence of both dual-role factors and stochastic data. A numerical example demonstrates the application of the proposed model.
- Chance-constrained data envelopment analysis
- Dual-role factors
- Third-party reverse logistics (3PL) providers
ASJC Scopus subject areas
- Computer Science Applications
- Artificial Intelligence