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Novel Spherical Fuzzy Eco-holonic Concept in Sustainable Supply Chain of Aviation Fuel

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Intelligent and Fuzzy Techniques in Aviation 4.0

Abstract

The objective of this chapter is to extend and combine two concepts of Eco-holonic structures and spherical fuzzy sets to introduce a novel concept of spherical fuzzy Eco-holonic structures. Both concepts consider different aspects of sustainability around the systems of real-world cases, so that caused an increase in a comprehensive analysis of the system. Eco-holonic structures help to consider many details of the system together with fuzzy logic, which assists to consider and evaluate the uncertainty around the system. Then, a multi attribute group decision making (MAGDM) method based on the spherical fuzzy Eco-holonic structure is proposed. Supply chain selection of aviation fuels is a hot topic these days and has very complexities. Sustainable supply chain (SSC) selection of aviation fuels is the most significant field of study among all aviation fuel supply chain problems because of many intuitive criteria that have to be considered through the decision-making procedure. Constructing and defining such an intuitive and comprehensive model for the aviation fuel supply chain is still out of sight, even though the significant research that have been done in this field. Another hardness of SSC in the aviation fuel is the satisfaction of all criteria based on such a complicated model. In this chapter, a spherical fuzzy Eco-holonic structure is defined for the sustainable supply chain of aviation fuels problem. Then, the proposed MAGDM method in SF Eco-holonic structure is applied to solve the SSC of aviation fuel problem. To show the feasibility and applicability of the proposed SF eco-holonic structure, it is applied in the aviation fuel SSC problem.

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Farid, F., Donyatalab, Y. (2022). Novel Spherical Fuzzy Eco-holonic Concept in Sustainable Supply Chain of Aviation Fuel. In: Kahraman, C., Aydın, S. (eds) Intelligent and Fuzzy Techniques in Aviation 4.0. Studies in Systems, Decision and Control, vol 372. Springer, Cham. https://doi.org/10.1007/978-3-030-75067-1_9

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