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Ying Luo

Researcher at Xiamen University

Publications -  6
Citations -  1336

Ying Luo is an academic researcher from Xiamen University. The author has contributed to research in topics: Rank reversals in decision-making & Fuzzy logic. The author has an hindex of 5, co-authored 6 publications receiving 1161 citations.

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On the extent analysis method for fuzzy AHP and its applications

TL;DR: It is found that the extent analysis method cannot estimate the true weights from a fuzzy comparison matrix and has led to quite a number of misapplications in the literature.
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Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making

TL;DR: A correlation coefficient (CC) and standard deviation (SD) integrated approach for determining the weights of attributes in multiple attribute decision making (MADM) and a global sensitivity analysis to the weights determined are proposed to ensure the stability of the best decision alternative or alternative ranking.
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On rank reversal in decision analysis

TL;DR: The fact that the rank reversal phenomenon occurs not only in the AHP but also in many other decision making approaches such as the Borda-Kendall method for aggregating ordinal preferences, the simple additive weighting method, the technique for order preference by similarity to ideal solution (TOPSIS) method, and the cross-efficiency evaluation method in data envelopment analysis (DEA).
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A note on group decision-making based on concepts of ideal and anti-ideal points in a fuzzy environment

TL;DR: This note illustrates with a numerical example that the method presented by Kuo et al. is not correct and can evaluate more than one decision alternative as the best even if they are not Pareto optimal at all.
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Aggregating preference rankings using OWA operator weights

TL;DR: This paper proposes the use of ordered weighted averaging (OWA) operator weights to aggregate preference rankings, which allows the weights associated with different ranking places to be determined in terms of a decision maker (DM)'s optimism level characterized by an orness degree.