Affiliations: Industrial Systems Engineering, University of Regina, Regina, SK, Canada
Correspondence:
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Corresponding author. Rene V. Mayorga, Industrial Systems Engineering, University of Regina, 3737 Wascana Parkway, Regina, SK, S4S 0A2, Canada. E-mail: [email protected].
Abstract: An efficient reverse logistics structure plays an important role in improving market competitiveness. The complexity of reverse logistics operations, customer service improvement, and costs elimination highlight the necessity of reverse operations outsourcing to the third-party reverse logistics providers (3PRLPs). Investigating and selecting an appropriate 3PRLP is recognized as a significant issue by manufacturers. This problem is affected by uncertainty, basically due to the vagueness intrinsic to the assessment of qualitative factors. This paper aims to propose a structured approach to prioritizing 3PRLPs based on sustainability criteria under fuzzy environment which accommodate the uncertainty associated with the vagueness of qualitative criteria. The proposed approach is composed of two main steps in which the first step employed the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) to select the effective criteria and the second step used Mamdani Fuzzy Inference System (FIS) model to cope with the vagueness that exists in the 3PRLPs evaluation process. If-then scenarios are employed to design rules of a FIS model which are devised by experts. The Experts’ knowledge about the problem is incorporated into the FIS system. This is a significant benefit of the proposed approach, in comparison with approaches which incorporate fuzzy set theory with multi-criteria decision-making models. An industrial case study is conducted to highlight the real-life applicability of the proposed approach. In addition, a sensitivity analysis is performed to confirm the robustness.
