Abstract
In this paper, authors propose a fast and efficient ranking method for interval grey numbers based on the idea of mean value and mean square deviation in statistics. If the degree of greyness of grey number is very small, the interval grey number is then big when the kernels of the interval grey numbers are equals. Authors extend data information weighted arithmetic averaging (WAA) operator, ordered weighted averaging (OWA) operator and hybrid weighted averaging operator (HWA) operator, meanwhile they propose interval grey numbers WAA operator, interval grey numbers OWA operator, and interval grey numbers HWA operator. According to these operators, authors develop an approach to solve grey multi-attribute multi-person decision-making problems, in which the attributive weights are completely known and the attributor values are interval grey numbers. Finally, an illustrative example is given.
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Wu, H., Mu, Y. (2013). Aggregation Operators of Interval Grey Numbers and Their Use in Grey Multi-Attribute Decision-Making. In: Wong, W.E., Ma, T. (eds) Emerging Technologies for Information Systems, Computing, and Management. Lecture Notes in Electrical Engineering, vol 236. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7010-6_12
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DOI: https://doi.org/10.1007/978-1-4614-7010-6_12
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