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A Lance Distance-Based MAIRCA Method for q-Rung Orthopair Fuzzy MCDM with Completely Unknown Weight Information
Volume 35, Issue 1 (2024), pp. 179–202
Pub. online: 24 April 2023      Type: Research Article      Open accessOpen Access
Received
1 December 2022
Accepted
1 April 2023
Published
24 April 2023

Abstract

The purpose of this manuscript is to develop a novel MAIRCA (Multi-Attribute Ideal-Real Comparative Analysis) method to solve the MCDM (Multiple Criteria Decision-Making) problems with completely unknown weights in the q-rung orthopair fuzzy (q-ROF) setting. Firstly, the new concepts of q-ROF Lance distance are defined and some related properties are discussed in this paper, from which we establish the maximizing deviation method (MDM) model for q-ROF numbers to determine the optimal criteria weight. Then, the Lance distance-based MAIRCA (MAIRCA-L) method is designed. In it, the preference, theoretical and real evaluation matrices are calculated considering the interaction relationship in q-ROF numbers, and the q-ROF Lance distance is applied to obtain the gap matrix. Finally, we manifest the effectiveness and advantage of the q-ROF MAIRCA-L method by two numerical examples.

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Biographies

Wang Haolun
https://orcid.org/0000-0001-7189-0264
hlwang71162@nchu.edu.cn

H. Wang is currently an assistant professor and full time academic member at the School of Economics and Management, Nanchang Hangkong University, Nanchang, China. He received an MSc degree in industrial engineering and a PhD degree in mechatronic engineering from Xiamen University, in 2009 and 2012, respectively. He has authored or co-authored more than 30 articles in professional journals. His current research interests include fuzzy sets, decision-making techniques, and supply chain management.

Xu Tingjun
https://orcid.org/0000-0002-1005-9183
2209125603001@stu.nchu.edu.cn

T. Xu is currently a master’s student at the School of Economic and Management, Nanchang Hangkong University, Nanchang, 330000, PR China. His research interests include q-rung orthopair fuzzy sets, multi-criteria decision making.

Pamucar Dragan
dragan.pamucar@fon.bg.ac.rs

D. Pamucar is an associate professor at the University of Belgrade, Faculty of Organizational Sciences. He received a PhD in applied mathematics with specialization in multi-criteria modelling and soft computing techniques, from the University of Defence in Belgrade, Serbia, in 2013, and an MSc degree from the Faculty of Transport and Traffic Engineering in Belgrade, 2009. His research interests are in the field of computational intelligence, multi-criteria decision making problems, neuro-fuzzy systems, fuzzy, rough and intuitionistic fuzzy set theory, neutrosophic theory. Application areas include wide range of logistics and engineering problems. He has written five books and over 220 research papers published in SCI indexed international journals including Experts Systems with Applications, Applied Soft Computing, Soft Computing, Computational Intelligence, Computers and Industrial Engineering, Engineering Applications of Artificial Intelligence, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions of Fuzzy Systems, IEEE Transactions on Transportation Electrification, Information Sciences and many more. According to Scopus and Stanford University, he is among the World top 2% of scientists as of 2020. According to WoS and Clarivate, he is among top 1% of highly cited researchers.

Li Xuxiang
2209125603034@stu.nchu.edu.cn

X. Li is currently a master’s student at the School of Economic and Management, Nanchang Hangkong University, Nanchang, 330000, PR China.

Feng Liangqing
https://orcid.org/0000-0003-3129-2889
lfeng@nchu.edu.cn

L. Feng was born in 1976. He received both his master’s degree in business administration and PhD in management science and engineering from Nanchang University, in 2012. He is currently a professor at the Department of Industrial Engineering, Nanchang Hangkong University. He has contributed more than 70 research articles. His major areas of research and expertise are quality management, logistics and supply chain management, manufacture service, management science and decision.


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Open access article under the CC BY license.

Keywords
Lance distance measure interaction operations q-ROF numbers MCDM

Funding
This work is supported by the Humanities and Social Sciences Foundation of Ministry of Education of the People’s Republic of China (No. 19YJC630164), the Postdoctoral Science Foundation of Jiangxi Province (No. 2019KY14), the National Natural Science Foundation, China (Nos. 71862025, 71362019), and Jiangxi Provincial “Double Thousand Plan” Philosophy and Social Science Leading Talent Project (jxsq2019203008).

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