Abstract
In this paper, we investigate the uncertain multiple attribute group decision making (MAGDM) problems in which the attributes and experts are in different priority level. Motivated by the idea of prioritized aggregation operators (Yager 2008), we develop some prioritized aggregation operators for aggregating uncertain information, and then apply them to develop some models for uncertain multiple attribute group decision making (MAGDM) problems in which the attributes and experts are in different priority level. Finally, a practical example about talent introduction is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Highlights
In many real and practical multiple attribute group decision making problems, attributes and decision makers have different priority level commonly. To overcome this drawback, Motivated by the ideal of prioritized aggregation operators (Yager 2008, 2009), in this paper, we propose some uncertain prioritized aggregation operators: uncertain prioritized weighted average (UPWA) operator, uncertain prioritized weighted geometric (UPWG) operator and uncertain prioritized weighted harmonic average (UPWHA) operator
The prominent characteristic of these proposed operators is that they take into account prioritization among the attributes and experts. We have utilized these operators to develop some approaches to solve the uncertain multiple attribute group decision making problems in which the attributes and experts are in different priority level
We have proposed three approaches to solve the uncertain multiple attribute group decision making problems in which the attributes and experts are in different priority level
Summary
A multiple attribute decision making problem is to find a desirable solution from a finite number of feasible alternatives assessed on multiple attributes, both quantitative and qualitative (Chen, Lee 2010a, 2010b; Chen, Niou 2011a, 2011b; Merigo, Gil-Lafuente 2009, 2011; Liu 2009; Merigo 2011b; Xu, Cai 2012; Xu 2002; Yager 1988; Zhang, Liu 2010; Zhou et al 2012) sion-making (i.e., multi-expert) is a typical decision-making activity where utilizing several experts alleviate some of the decision-making difficulties due to the problem’s complexity and uncertainty (Wei 2010a, 2010b, 2011a, 2011b, 2012; Xu, Cai 2012; Ye 2011a, 2011b). Merigo et al (2012) developed a new decision making approach for dealing with uncertain information and apply it in tourism management They proposed the uncertain induced ordered weighted averaging – weighted averaging (UIOWAWA) operator and studied some of the main advantages and properties of the new aggregation such as the uncertain arithmetic UIOWA (UA-UIOWA) and the uncertain arithmetic UWA (UAUWA). It provides a very general formulation that includes as special cases a wide range of aggregation operators and aggregates the input arguments taking the form of intervals rather than exact numbers They further generalize the UGOWA operator to obtain the uncertain generalized hybrid averaging operator, the quasi uncertain ordered weighted averaging operator and the uncertain generalized Choquet integral aggregation operator. We conclude the paper and give some remarks
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