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Soft Computing

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31.01.2020 | Methodologies and Application

A decision support model based on the combined structure of DEMATEL, QFD and fuzzy values

verfasst von: Morteza Yazdani, Z. X. Wang, Felix T. S. Chan

Erschienen in: Soft Computing | Ausgabe 16/2020

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Abstract

Uncertainty and risk are inevitable issues in decision making in supply chain systems. In knowledge-based communities, uncertain conditions are recognized, analyzed and eliminated using wide range of concepts and approaches. One intelligent tool to aid in decreasing impreciseness and in delivering an acceptable level of accuracy is fuzzy logic. This study reports a new version of the fuzzy multiple criteria decision-making family. The decision-making trial and evaluation laboratory (DEMATEL) is extended for the first time with interval fuzzy values and then integrated as an input for the quality function deployment (QFD) mechanism. Although the application of decision-making tools in the supply chain and its sustainable development is undeniable, the implementation of fuzzy decision support systems in sustainable supply chains still demands more research work. This study develops an IT2F DEMATEL-QFD model to evaluate and rank sustainable supply chain drivers in a group decision-making environment. The proposed fuzzy decision model is connected to a real research project for eliminating risks in the supply chain related to agricultural production systems. Sensitivity analysis confirms the stability of the model. It is concluded that the outcomes and advantages of the newly developed model will profit academic and non-academic partners.

Vorheriger Artikel Multidisciplinary design optimization of an aircraft by using knowledge-based systems

Nächster Artikel Development of operation multi-objective model of dam reservoir under conditions of temperature variation and loading using NSGA-II and DANN models: a case study of Karaj/Amir Kabir dam

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Titel: A decision support model based on the combined structure of DEMATEL, QFD and fuzzy values
verfasst von: Morteza Yazdani
Z. X. Wang
Felix T. S. Chan
Publikationsdatum: 31.01.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 16/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-020-04685-2

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