RT info:eu-repo/semantics/bookPart
T1 Fuzzy logic-based approaches in supply chain risk management: a review
A1 Díaz Curbelo, Alina
A1 Gento Municio, Ángel Manuel
A1 Espin Andrade, Rafael Alejandro
K1 Fuzzy sets
K1 Risk management
K1 Uncertainty
K1 Subjectivity
K1 Supply chain
K1 Decision making
AB Uncertainty is inherent in the supply chains nature. In the context of various uncertainties, risk management plays a crucial role in effective supply chain management. The uncertainty involved in the risk assessment process can be divided into two types: random uncertainty and epistemic uncertainty. The fuzzy theory has been applied to address uncertainties in this context. The purpose of this paper is to develop a literature review of the major contributions of fuzzy logic in addressing uncertainty in supply chain risk management approaches. The results revealed that integration with disruptive analysis tools and multi-criteria decision-making methods are the most common types adopted, with the increasing trend of Petri nets and Bayesian approaches. The reviewed literature highlights some limitations related to the holistic complexity of risks in supply chains, the dynamic nature of the environment, and the reliability of the knowledge base in the assessment. In that sense, these observations reveal interesting future lines of research.
PB Springer
SN 978-3-030-73818-1
YR 2021
FD 2021
LK https://uvadoc.uva.es/handle/10324/73881
UL https://uvadoc.uva.es/handle/10324/73881
LA eng
NO Witold Pedrycz, Luis Martínez, Rafael Alejandro Espin-Andrade, Gilberto Rivera, Jorge Marx Gómez (eds.). Computational  Intelligence for Business Analytics. 2021, p. 79-94.
NO Producción Científica
DS UVaDOC
RD 25-ene-2025