Abstract
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.
Original language | English |
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Pages (from-to) | 12231-12236 |
Number of pages | 6 |
Journal | Expert Systems with Applications |
Volume | 38 |
Issue number | 10 |
DOIs | |
Publication status | Published - Sept 15 2011 |
Keywords
- Chance-constrained data envelopment analysis
- Dual-role factors
- Third-party reverse logistics (3PL) providers
ASJC Scopus subject areas
- Engineering(all)
- Computer Science Applications
- Artificial Intelligence