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Informatica


A New Decision Making Method Using Interval-Valued Intuitionistic Fuzzy Cosine Similarity Measure Based on the Weighted Reduced Intuitionistic Fuzzy Sets
Volume 31, Issue 2 (2020), pp. 399–433
Pub. online: 27 March 2020      Type: Research Article      Open accessOpen Access
Received
1 March 2019
Accepted
1 February 2020
Published
27 March 2020

Abstract

In this paper, we develop a new flexible method for interval-valued intuitionistic fuzzy decision-making problems with cosine similarity measure. We first introduce the interval-valued intuitionistic fuzzy cosine similarity measure based on the notion of the weighted reduced intuitionistic fuzzy sets. With this cosine similarity measure, we are able to accommodate the attitudinal character of decision-makers in the similarity measuring process. We study some of its essential properties and propose the weighted interval-valued intuitionistic fuzzy cosine similarity measure.
Further, the work uses the idea of GOWA operator to develop the ordered weighted interval-valued intuitionistic fuzzy cosine similarity (OWIVIFCS) measure based on the weighted reduced intuitionistic fuzzy sets. The main advantage of the OWIVIFCS measure is that it provides a parameterized family of cosine similarity measures for interval-valued intuitionistic fuzzy sets and considers different scenarios depending on the attitude of the decision-makers. The measure is demonstrated to satisfy some essential properties, which prepare the ground for applications in different areas. In addition, we define the quasi-ordered weighted interval-valued intuitionistic fuzzy cosine similarity (quasi-OWIVIFCS) measure. It includes a wide range of particular cases such as OWIVIFCS measure, trigonometric-OWIVIFCS measure, exponential-OWIVIFCS measure, radical-OWIVIFCS measure. Finally, the study uses the OWIVIFCS measure to develop a new decision-making method to solve real-world decision problems with interval-valued intuitionistic fuzzy information. A real-life numerical example of contractor selection is also given to demonstrate the effectiveness of the developed approach in solving real-life problems.

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Biographies

Verma Rajkumar
rverma@fen.uchile.cl

R. Verma received the MSc degree in mathematics from Chaudhary Charan Singh University University, Meerut (U.P.), India, in 2006, and the PhD degree in applied mathematics with a speciality in information theory and computational intelligence techniques from Jaypee Institute of Information Technology (Deemed University), Noida (U.P.), India, in 2014. He is currently a postdoctoral research fellow at the Department of Management Control and Information Systems, University of Chile, Santiago, Chile. He has authored over 45 research articles published in refereed international journals including the International Journal of Intelligent Systems, Kybernetika, Journal of Intelligent and Fuzzy Systems, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, International Journal of Machine Learning and Cybernetics, Neural Computing and Applications, Informatica. He has also authored five book chapters. He is currently interested in information measures, aggregation operators, multiple attribute group decision making, computational intelligence techniques, and computing with words.

Merigó José M.
jmerigo@fen.uchile.cl

J. M.Merigó (PhD 2009) is a professor at the School of Information, Systems, and Modelling at the Faculty of Engineering and Information Technology at the University of Technology, Sydney (Australia). Before joining UTS, he was a full professor at the Department of Management Control and Information Systems at the University of Chile. Previously, he was a senior research fellow at the Manchester Business School, University of Manchester (UK) and an assistant professor at the Department of Business Administration at the University of Barcelona (Spain). He holds a masters and a PhD degree in business administration from the University of Barcelona. He also holds a bachelors degree of science and of social sciences in economics and a masters degree in European business administration and business law from Lund University (Sweden).

He has published more than 400 articles in journals, books and conference proceedings. He is on the editorial board of several journals. He has also been a guest editor for several international journals, member of the scientific committee of several conferences and reviewer in a wide range of international journals. Recently (2015–2018), Clarivate Analytics (previously Thomson & Reuters) has distinguished him as a highly cited researcher in computer science. He is currently interested in decision making, aggregation operators, computational intelligence, bibliometrics and applications in business and economics.


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© 2020 Vilnius University
Open access article under the CC BY license.

Keywords
interval-valued intuitionistic fuzzy sets weighted reduced intuitionistic fuzzy sets cosine similarity measure ordered weighted average operator multiple attribute decision-making

Funding
The first author would like to acknowledge the Postdoctoral Research Financial support from Project 3170556 provided by the Chilean Government (Conicyt) through the Fondecyt Postdoctoral Program.

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