A novel hybrid multiple attribute decision-making approach for outsourcing sustainable reverse logistics

Navid Zarbakhshnia, Yong Wu*, Kannan Govindan, Hamed Soleimani

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


In this paper, we propose a novel hybrid multiple attribute decision-making (MADM) approach, which includes fuzzy analytic hierarchy process (fuzzy AHP) and gray multi-objective optimization by ratio analysis (MOORA-G). By using fuzzy and gray numbers, we successfully deal with the qualitative and uncertain inputs that often arise from real-world decision-making process. We adopt this hybrid approach to take the advantages offered by both methods, and designate the former for weighting the considered criteria, and the latter for ranking the alternatives. To demonstrate the performance of the proposed hybrid approach, we apply it to a case study on the selection of third-party reverse logistics providers (3PRLPs) for a car parts manufacturing company and benchmark it with the MOORA method. The outcome of this study indicates that our proposed approach can offer more viable performance when facing qualitative data and input uncertainties, and consequently, lends itself to a wider range of applications.

Original languageEnglish
Article number118461
JournalJournal of Cleaner Production
Number of pages16
Publication statusPublished - 1. Jan 2020



  • Fuzzy analytic hierarchy process (fuzzy AHP)
  • Gray multi-objective optimization by ratio analysis (MOORA-G)
  • Multiple attribute decision-making (MADM)
  • Sustainable reverse logistics
  • Third-party reverse logistics provider (3PRLP)

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