An overview of methods for determining OWA weights

By Zeshui Xu. International Journal of Intelligent Systems, 2005

816 citations recorded by the source corpus.

Subfields: Industrial and Manufacturing Engineering, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/8defe55e45e14c593555aa45bfbc5507df48cae7

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Citations in the corpus

Intuitionistic Fuzzy Aggregation Operators (2007, methodology): “The IFOWA weights can be determined similar to the OWA weights (for example, we can use the normal distribution based method to determine the IFOWA weights [48]).”
Dynamic intuitionistic fuzzy multi-attribute decision making (2008, methodology): “The normal distribution based method has the following properties [19]:”
Hesitant fuzzy information aggregation in decision making (2011, methodology): “Aggregation operators for hesitant fuzzy information Since its appearance, the ordered weighted averaging (OWA) operator, introduced by Yager [14], has received more and more attention [15–21].”
The Induced Generalized OWA Operator (2009, methodology): “A special type of centered IGOWA operator is the Gaussian IGOWA weights which follows the same methodology than the Gaussian OWA weights suggested by Xu [14].”
A Novel Approach towards Bipolar Soft Sets and Their Applications (2020, methodology): “According to Xu [48], the weight vector w � ( w 1 , w 2 , w 3 , . . . , w n ) T can also be calculated as where In this case, Example 5 takes the following form (Tables 7 and 8).”
Linguistic Pythagorean fuzzy sets and its applications in multiattribute decision‐making process (2018, neutral): “= ⎜⎜⎜⎝st √ 1− n ∏ i=1 (1−θ2 (i)∕t 2)wi , s t n ∏ i=1 (σ(i)∕t)i ⎟⎟⎟⎠ (10)”
Extension of the TOPSIS method for decision making problems under interval-valued intuitionistic fuzzy environment (2011, methodology): “155) be its weight vector derived by the normal distribution based method [37]) to aggregate the individual interval-valued intuitionistic fuzzy decision matrices R 1⁄4 ðr ij Þ5 4ðk 1⁄4 1;2;3;4Þ into the collective interval-valued intuitionistic fuzzy decision matrix R = (rij)5 4 (Table 5).”
New decision-making techniques and their application in the selection of financial products (2010, methodology): “The formulation of these families is straightforward, as indicated in Remarks 2–7 and in [1–4,22–24,27–30,34,35,37,40,48–51,54,55].”
Aggregation Functions: A Guide for Practitioners (2007, background): “The problem of identification of weights of OWA functions was studied by several authors [93, 100, 259, 276].”
Some geometric aggregation operators based on intuitionistic fuzzy sets (2006, methodology): “Many methods can be used to determine the OWG weights (please see Xu (2005) for more details).”
Some Hamacher Aggregation Operators Based on the Interval-Valued Intuitionistic Fuzzy Numbers and Their Application to Group Decision Making (2014, methodology): “For example, the method proposed by Xu [24] is shown as follows:”
Stochastic-fuzzy multi criteria decision making for robust water resources management (2009, methodology): “Xu (2005) gives a general overview of the different methods for obtaining the order weights.”
Induced generalized intuitionistic fuzzy operators (2011, methodology): “Utilize the normal distribution based method [30] to determine the weight vector Wqk with qk elements: W3 1⁄4 ð0:4;0:4;0:2Þ; W4 1⁄4 ð0:3;0:3;0:2;0:2Þ: Step 4.”
Prioritized aggregation operators (2008, background): “Many of the techniques available for calculating the OWA weights [12] can be tailored for this particular application.”