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Fuzzy Logic-Based Approaches in Supply Chain Risk Management: A Review

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Computational Intelligence for Business Analytics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 953))

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Abstract

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.

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Authors and Affiliations

  1. University of Valladolid, 47011, Valladolid, Spain

    Alina Díaz-Curbelo & Ángel Manuel Gento Municio

  2. Autonomous University of Cohauila, 25280, Saltillo, Coahuila, Mexico

    Rafael Alejandro Espin-Andrade

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  1. Alina Díaz-Curbelo
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  2. Ángel Manuel Gento Municio
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  3. Rafael Alejandro Espin-Andrade
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Correspondence to Alina Díaz-Curbelo .

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Editors and Affiliations

  1. Electrical and Computer Engineering, University of Alberta, Canada, AB, Canada

    Witold Pedrycz

  2. Department of Computer Science, School of Computing, Universidad de Jaén, Jaén, Spain

    Luis Martínez

  3. Accounting and Administration Faculty, Centre of Innovation Management Research for Entrepreneurial and Regional Development (CIGIDER), Autonomous University of Coahuila, Coah, Mexico

    Rafael Alejandro Espin-Andrade

  4. División Multidisciplinaria de Ciudad Universitaria, Universidad Autónoma de Ciudad Juárez, Chihuahua, Mexico

    Gilberto Rivera

  5. Department of Computing Science, Business Information Systems/ VLBA, Carl von Ossietzky Universität Oldenburg, Oldenburg, Niedersachsen, Germany

    Jorge Marx Gómez

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Díaz-Curbelo, A., Gento Municio, Á.M., Espin-Andrade, R.A. (2021). Fuzzy Logic-Based Approaches in Supply Chain Risk Management: A Review. In: Pedrycz, W., Martínez, L., Espin-Andrade, R.A., Rivera, G., Marx Gómez, J. (eds) Computational Intelligence for Business Analytics. Studies in Computational Intelligence, vol 953. Springer, Cham. https://doi.org/10.1007/978-3-030-73819-8_5

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