Multi-attribute Group Decision-Making Method Based on Cloud Distance Operators With Linguistic Information

Multi-attribute Group Decision-Making Method Based on Cloud Distance Operators With Linguistic... Linguistic terms can easily express the qualitative information given by decision makers, but such a qualitative concept cannot be directly calculated like exact number. Thus, it needs to be translated to a quantitative concept. The cloud model can do the transformation well which has the advantage of describing the randomness and fuzziness of qualitative concepts synthetically. The distance operator is good at indicating internal relationship between values and reflecting the degree of deviation. Therefore, in this paper, we firstly introduce the conversion method from linguistic terms to cloud model, then propose a series of cloud distance aggregation operators such as cloud weighted averaging distance operator, cloud weighted geometric averaging distance operator, and cloud generalized weighted averaging distance operator (CGWAD), and prove some desired properties. Further, we develop a group decision-making method based on the CGWAD operator in which the TOPSIS method is extended to rank those alternatives. Finally, a numerical example is given to verify the practicability of the newly developed method. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Fuzzy Systems Springer Journals

Multi-attribute Group Decision-Making Method Based on Cloud Distance Operators With Linguistic Information

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2016 by Taiwan Fuzzy Systems Association and Springer-Verlag Berlin Heidelberg
Subject
Engineering; Computational Intelligence; Artificial Intelligence (incl. Robotics); Operations Research, Management Science
ISSN
1562-2479
eISSN
2199-3211
D.O.I.
10.1007/s40815-016-0279-5
Publisher site
See Article on Publisher Site

Abstract

Linguistic terms can easily express the qualitative information given by decision makers, but such a qualitative concept cannot be directly calculated like exact number. Thus, it needs to be translated to a quantitative concept. The cloud model can do the transformation well which has the advantage of describing the randomness and fuzziness of qualitative concepts synthetically. The distance operator is good at indicating internal relationship between values and reflecting the degree of deviation. Therefore, in this paper, we firstly introduce the conversion method from linguistic terms to cloud model, then propose a series of cloud distance aggregation operators such as cloud weighted averaging distance operator, cloud weighted geometric averaging distance operator, and cloud generalized weighted averaging distance operator (CGWAD), and prove some desired properties. Further, we develop a group decision-making method based on the CGWAD operator in which the TOPSIS method is extended to rank those alternatives. Finally, a numerical example is given to verify the practicability of the newly developed method.

Journal

International Journal of Fuzzy SystemsSpringer Journals

Published: Nov 23, 2016

References

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