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Article type: Research Article
Authors: Sang, Xiuzhi | Liu, Xinwang | Chen, Lianghua
Affiliations: School of Economics and Management, Southeast University, Nanjing, Jiangsu, China
Note: [] Corresponding authors. Xiuzhi Sang, Xinwang Liu and Lianghua Chen, School of Economics and Management, Southeast University, Nanjing, Jiangsu 210096, China. E-mails: [email protected] (X.Sang), [email protected] (X.Liu), [email protected] (L. Chen).
Note: [] Corresponding authors. Xiuzhi Sang, Xinwang Liu and Lianghua Chen, School of Economics and Management, Southeast University, Nanjing, Jiangsu 210096, China. E-mails: [email protected] (X.Sang), [email protected] (X.Liu), [email protected] (L. Chen).
Note: [] Corresponding authors. Xiuzhi Sang, Xinwang Liu and Lianghua Chen, School of Economics and Management, Southeast University, Nanjing, Jiangsu 210096, China. E-mails: [email protected] (X.Sang), [email protected] (X.Liu), [email protected] (L. Chen).
Abstract: We develop the parametric weighted ordered weighted average (WOWA) operator in dynamic decision problems represented by multi-criteria decision tree, which combines the regular increasing monotonic (RIM) quantifiers with piecewise linear function. The parametric WOWA operator with piecewise linear function can be used to represent various preferences of the decision makers in the forms of risk pessimistic, risk neutral and risk optimistic, respectively. The expected utility theory becomes a special case of it with risk neutral attitude. Meanwhile, some properties of the parametric WOWA operator with piecewise linear function are provided and the advantages of it in solving dynamic decision making problems are summarized. Different attitudes of the decision makers can be implemented by changing the values of parameter in parametric WOWA operators under different application contexts. Finally, an example is introduced to illustrate our theoretical results with decision tree for introducing and pricing new product.
Keywords: Parametric WOWA operator, RIM quantifiers, piecewise linear function, decision tree, dynamic decision making
DOI: 10.3233/IFS-131016
Journal: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 1, pp. 475-486, 2014
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