Intuitionistic Linguistic Multiple Attribute Decision-making Based on Heronian Mean Method and Its Application to Evaluation of Scientific Research Capacity
Chonghui Zhang 1, Weihua Su 1 * , Shouzhen Zeng 2
More Detail
1 College of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, CHINA2 School of Business, Ningbo University, Ningbo 315211, CHINA* Corresponding Author

This article belongs to the special issue "Problems of Application Analysis in Knowledge Management and Science-Mathematics-Education".

Abstract

The main focus of this paper is to investigate intuitionistic linguistic information fusion based on Heronian mean. Two new intuitionistic linguistic aggregation operators called intuitionistic linguistic generalized Heronian mean (ILGHM) and intuitionistic linguistic generalized weighted Heronian mean (ILGWHM) operators, are introduced. The ILGHM and ILGWHM operators are characterized by the ability to deal with the intuitionistic linguistic multiple attribute decision making problems in which the attributes are interactive. Some desired properties and special cases with respect to the different parameter values in the developed operators are studied. Furthermore, a method based on the proposed operators is developed to deal with multiple attribute group decision making (MAGDM) method problems. Finally, an illustrative example concerning evaluation of scientific research capacity is provided to illustrate the decision-making process and to discuss the influences of different parameters on the decision-making results.

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, 2017, Volume 13, Issue 12, 8017-8025

https://doi.org/10.12973/ejmste/77933

Publication date: 22 Nov 2017

Article Views: 1812

Article Downloads: 821

Open Access References How to cite this article