The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making

Chen, Ting‐Yu; Chang, Chi-Jen; Lu, Jui-fen Rachel

doi:10.1016/j.ejor.2012.11.038

Cited by 203 publications

(110 citation statements)

References 49 publications

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“…Chen [35] suggested an interval-valued intuitionistic fuzzy QUALIFLEX approach using likelihood-based comparison method to resolve MCDM issues. In addition, other meaningful extensions of the QUALIFLEX technique in previous studies include the interval-valued intuitionistic fuzzy QUALIFLEX [36], the interval type-2 fuzzy QUALIFLEX [37], and the hesitant trapezoidal fuzzy QUALIFLEX [38].…”

Section: Applications Of Qualiflex Methodsmentioning

confidence: 99%

Green Supplier Evaluation and Selection Using Cloud Model Theory and the QUALIFLEX Method

Wang

Liu

et al. 2017

Sustainability

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Nowadays, companies have to improve their practices in the management of green supply chain with increased awareness of environmental issues worldwide. Selecting the optimum green supplier is crucial for green supply chain management, which is a challenging multi-criteria decision making (MCDM) problem. Moreover, while evaluating the performance of alternative suppliers, decision makers tend to determine their assessments using linguistic descriptors due to experts' vague knowledge and information deficiency. Therefore, this paper develops an integrated MCDM model based on the cloud model and QUALIFLEX (qualitative flexible multiple criteria method) approach to assess the green performance of companies under economic and environmental criteria. For the introduced model, the linguistic terms, expressed in normal clouds, are utilized to assess alternatives against each selection criterion. A linear programming model is established to compute the weights of criteria with unknown or incompletely known weight information. An extended QUALIFLEX approach is proposed and used to select the most suitable green supplier. Finally, the proposed green supplier selection method is demonstrated by an empirical example of an auto manufacturer to confirm its rationality and effectiveness.

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Section: Applications Of Qualiflex Methodsmentioning

confidence: 99%

Green Supplier Evaluation and Selection Using Cloud Model Theory and the QUALIFLEX Method

Wang

Liu

et al. 2017

Sustainability

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“…In another paper, Cebi and Otay 39 introduced the application of fuzzy TOPSIS method with Interval Type-2 fuzzy sets on a facility location selection problem for a cement factory. Chen et al 41 extended the QUALIFLEX method for dealing with MCDM problems in an Interval Type-2 environment. The quoted study explicated the convenience and practicability of the presented techniques for a medical (acute inflammatory demyelinating disease) MCDM problem.…”

Section: Literature Survey Of Type-2 Methodsmentioning

confidence: 99%

Evaluation of Knowledge Management Tools by Using An Interval Type-2 Fuzzy TOPSIS Method

Büyüközkan¹,

Parlak²,

Tolga³

2016

IJCIS

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Knowledge management (KM) systems can provide businesses a wide range of advantages and efficiency improvements. Increasing competition forces companies to seek new ways to streamline their processes and manage their information and knowledge better, leading to increased demand for KM solutions. Considering various needs of organizations and diverse features of available KM alternatives, choosing the most suitable KM tool is an important decision for businesses. The contribution of this paper to the KM literature is a KM evaluation framework for decision makers to compare available KM products of different vendors by first identifying relevant evaluation criteria and then proposing a group decision making framework using the Interval Type-2 TOPSIS technique. This method has more flexibility in handling uncertainties compared to the Type-1 fuzzy sets and enables decision makers to effectively analyze, compare and select the most appropriate KM tools. The framework is also used in a case study for the sake of demonstrating its potential in businesses.

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“…Type-2 fuzzy sets are also increasingly used in multiattribute decision making problems because of their ability in defining membership functions. Chen et al [55] develop an extended QUALIFLEX method for handling multiple criteria decision-making problems in the context of interval type-2 fuzzy sets. QUALIFLEX, a generalization of Jacquet-Lagreze's permutation method, is a useful outranking method in decision analysis because of its flexibility with respect to cardinal and ordinal information.…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

Strategic Decision Selection Using Hesitant fuzzy TOPSIS and Interval Type-2 Fuzzy AHP: A case study

Onar¹,

Öztayşi²,

Kahraman³

2014

IJCIS

144

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Strategic decisions such as mergers, acquisitions and joint ventures have a strong effect on firm performance. In order to be successful in highly competitive environments firms have to make right and on time strategic decisions. However, the nature of making the right strategic decision is complex and unstructured since there are many factors affecting such decisions. Moreover these factors are usually hard and vague to evaluate numerically. This study tries to develop a multicriteria decision-making model which considers both the complexity and vagueness of strategic decisions. The weights of the factors are determined by interval type-2 Fuzzy Analytic Hierarchy Process (AHP) and then the best strategy is selected by Hesitant Fuzzy TOPSIS using the determined weights. An application to a multinational consumer electronics company is presented.

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The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making

Cited by 203 publications

References 49 publications

Green Supplier Evaluation and Selection Using Cloud Model Theory and the QUALIFLEX Method

Green Supplier Evaluation and Selection Using Cloud Model Theory and the QUALIFLEX Method

Evaluation of Knowledge Management Tools by Using An Interval Type-2 Fuzzy TOPSIS Method

Strategic Decision Selection Using Hesitant fuzzy TOPSIS and Interval Type-2 Fuzzy AHP: A case study

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