Multi-Criteria Decision Making in Reverse Logistics
Summary
Reverse logistics encompasses the processes by which products and materials are returned, reclaimed, remanufactured or recycled, thereby closing the supply chain loop and supporting sustainability objectives. The inherent complexity arises from the need to balance economic, environmental and service quality criteria under conditions of uncertainty and conflicting stakeholder priorities. Multi-criteria decision making (MCDM) provides a structured framework for evaluating alternative return-flow strategies, facility locations, transportation modes and third-party reverse logistics providers. Common approaches integrate weight-assigning techniques (such as AHP or entropy methods) with ranking algorithms (for example TOPSIS, VIKOR or MULTIMOORA) to reflect both subjective expert judgement and objective data. The application of fuzzy-set theories, neutrosophic logic and advanced aggregation operators further enhances the capacity to model vagueness, inter-criterion interaction and incomplete information. Practical implementations demonstrate how hybrid MCDM models can guide the efficient selection of remanufacturing partners, optimise network design and prioritise criteria such as lead time, cost, environmental impact and customer satisfaction. By unifying quantitative and qualitative factors, MCDM in reverse logistics underpins more resilient, circular supply chains with demonstrable economic and societal benefits.
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Multi-Criteria Decision Making in Reverse Logistics publication trend
The graph below shows the total number of articles in multi-criteria decision making in reverse logistics across all publications each year (not limited to Nature Index journals).
Technical terms
Multi-Criteria Decision Making (MCDM): A set of mathematical and analytical techniques for evaluating alternatives against multiple, often conflicting, criteria.
Reverse Logistics: The process of planning, implementing and controlling the flow of returned products and materials for recovery or disposal.
Fuzzy Sets: Mathematical constructs that allow partial membership of elements, modelling uncertainty and vagueness in human judgement.
q-Rung Orthopair Fuzzy Sets: An extension of fuzzy sets that permits independent degrees of membership and non-membership up to a power parameter, improving flexibility in uncertainty representation.
MULTIMOORA: A multi-objective optimisation technique combining ratio systems, reference-point approaches and full multiplicative forms to rank alternatives.
WASPAS: A hybrid MCDM method that aggregates weighted sum and weighted product models to evaluate and prioritise options.
References
- An integrated group decision-making framework for assessing S3PRLPs based on MULTIMOORA-WASPAS with q-rung orthopair fuzzy information. Artificial Intelligence Review (2024).
- Outsourcing Reverse Logistics for E-Commerce Retailers: A Two-Stage Fuzzy Optimization Approach. Axioms (2021).
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