Journal Article10.1016/J.ESWA.2010.04.066
A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods
TL;DR: An evaluation model based on the fuzzy analytic hierarchy process and the technique for order performance by similarity to ideal solution, fuzzy TOPSIS is developed to help the industrial practitioners for the performance evaluation in a fuzzy environment.
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Abstract: Multiple criteria decision-making (MCDM) research has developed rapidly and has become a main area of research for dealing with complex decision problems. The purpose of the paper is to explore the performance evaluation model. This paper develops an evaluation model based on the fuzzy analytic hierarchy process and the technique for order performance by similarity to ideal solution, fuzzy TOPSIS, to help the industrial practitioners for the performance evaluation in a fuzzy environment where the vagueness and subjectivity are handled with linguistic values parameterized by triangular fuzzy numbers. The proposed method enables decision analysts to better understand the complete evaluation process and provide a more accurate, effective, and systematic decision support tool.
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Citations
Cloud Service Selection Using TOPSIS and Fuzzy TOPSIS with AHP and ANP
Akshay Jaiswal,R. B. Mishra +1 more
- 13 Jan 2017
TL;DR: To rank cloud services based on quantified QoS (Quality of Service) attributes using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy TOPSIS, and comparing them to find out which method suits more in different scenarios.
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Integrated SEM-FTOPSIS framework for modeling and prioritization of risk sources in medical device development process
Abstract: Purpose
The purpose of this paper is to outline and prioritizes risk sources in medical device development (MDD) process using an integrated “structural equation modeling” (SEM) and fuzzy “technique for order performance by similarity to ideal solution (TOPSIS)” framework.
Design/methodology/approach
Risk sources which deter MDD process are explored through literature review. Initial structural model is proposed, factor loadings are determined by exploratory factor analysis and model fit is established by confirmatory factor analysis. Further, the sources are ranked using FTOPSIS, and sensitivity analysis is carried to check robustness of results.
Findings
The sources of risks have catastrophic effect on MDD process. The initial SEM model developed based on survey of experts is found reliable and valid which breaks up the risk sources into three categories – internal sources of risks, user-related sources of risks and third-party-related sources of risks. The risk sources are ranked and prioritized based on perspective of experts from the categories using FTOPSIS; unmet user needs/requirements is found as the most important source of risk. Results of sensitivity analysis confirm that the factors are relatively less sensitive to criteria weights confirming reliability of initial solution.
Research limitations/implications
The proposed methodology combines qualitative and quantative approaches, making it little complex and lengthy, but results in dual confirmation.
Practical implications
The outcomes of this research will be of prime use for MDD industries to mitigate risk sources. It will help to increase the success rate of MDD.
Originality/value
Integrated SEM-FTOPSIS provides a unique and effective structural modeling-based decision support tool. The framework can be effectively utilized in other domains, and failure events of medical devices can be potentially controlled by applying risk mitigation measures.
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A Two Phase Integrated Fuzzy Decision-Making Framework for Green Supplier Selection in the Coffee Bean Supply Chain
Ngoc Bao Tu Nguyen,Gu-Hong Lin,Thanh-Tuan Dang +2 more
- 12 Aug 2021
TL;DR: The work presented provides insight to decision-makers of supplier selection that helps determine significant GSS criteria and aids in the minimization of environmental risks to society arising from the supply chain on corporate sustainability standards.
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An integrated fuzzy framework for analyzing barriers to the implementation of continuous improvement in manufacturing
TL;DR: A novel integrated fuzzy framework for analyzing the barriers to the implementation of CI in manufacturing companies shows “low cooperation and integration of the team in CI activities” is the most important barrier in CI implementation.
Risk Analysis for Critical Infrastructures Using Fuzzy TOPSIS
TL;DR: The fuzzy TOPSIS as a fuzzy multi criteria decision making technique is adopted to determine the weights of each criterion and the importance of alternatives with respect to criteria and the proposed model demonstrates a significant improvement in comparison with conventional RAMCAP.
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