A new chance-constrained data envelopment analysis for selecting third-party reverse logistics providers in the existence of dual-role factors

Majid Azadi, Reza Farzipoor Saen

Research output: Contribution to journalArticlepeer-review

110 Citations (Scopus)

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 languageEnglish
Pages (from-to)12231-12236
Number of pages6
JournalExpert Systems with Applications
Volume38
Issue number10
DOIs
Publication statusPublished - Sep 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

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