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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.

References

 
Atanassov, K.T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets Systems, 20, 87–96.
 
Akram, M., Shumaiza (2021). Multi-criteria decision making based on q-rung orthopair fuzzy PROMETHEE approach. Iranian Journal of Fuzzy Systems, 18(5), 107–127.
 
Ali, J. (2022). A q-rung orthopair fuzzy MARCOS method using novel score function and its application to solid waste management. Applied Intelligence, 52(8), 8770–8792.
 
Alkan, N., Kahraman, C. (2021). Evaluation of government strategies against COVID-19 pandemic using q-rung orthopair fuzzy TOPSIS method. Applied Soft Computing, 110, 107653.
 
Arya, V., Kumar, S. (2021). Extended TODIM method based on VIKOR for q-rung orthopair fuzzy information measures and their application in MAGDM problem of medical consumption products. International Journal of Intelligent Systems, 36(11), 6837–6870.
 
Aydemir, S.B., Gunduz, S.Y. (2020). Extension of multi-Moora method with some q-rung orthopair fuzzy Dombi prioritized weighted aggregation operators for multi attribute decision making. Soft Computing, 24(24), 18545–18563.
 
Bashir, Z., Ali, J., Rashid, T. (2021). Consensus-based robust decision making methods under a novel study of probabilistic uncertain linguistic information and their application in Forex investment. Artificial Intelligence Review, 54, 2091–2132.
 
Boral, S., Howard, I., Chaturvedi, S.K., McKee, K., Naikan, V.N.A. (2020). An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA. Engineering Failure Analysis, 108, 104195.
 
Bozanic, D., Randelovic, A., Radovanovic, M., Tesic, D. (2020). A hybrid LBWA-IR-MAIRCA multi-criteria decision-making model for determination of constructive elements of weapons. FACTA Universitatis-Series Mechanical Engineering, 18(3), 399–418.
 
Cuong, B.C. (2014). Picture fuzzy sets. Journal of Computer Science and Cybernetics, 30(4), 409–420.
 
Chatterjee, K., Pamucar, D., Zavadskas, E.K. (2018). Evaluating the performance of suppliers based on using the R’AMATEL-MAIRCA method for green supply chain implementation in electronics industry. Journal of Cleaner Production, 184, 101–129.
 
Chen, L.X., Luo, N.F., Gou, X.L. (2021). A novel q-rung orthopair fuzzy TODIM approach for multi-criteria group decision making based on Shapley value and relative entropy. Journal of Intelligent & Fuzzy Systems, 40(1), 235–250.
 
Darko, A.P., Liang, D.C. (2020). Some q-rung orthopair fuzzy Hamacher aggregation operators and their application to multiple attribute group decision making with modified EDAS method. Engineering Applications of Artificial Intelligence, 87, 103259.
 
Deveci, M., Gokasar, I., Brito-Parada, P.R. (2022a). A comprehensive model for socially responsible rehabilitation of mining sites using q-rung orthopair fuzzy sets and combinative distance-based assessment. Expert Systems with Applications, 200, 117155.
 
Deveci, M., Gokasar, I., Pamucar, D., Coffman, D., Papadonikolaki, E. (2022b). Safe E-scooter operation alternative prioritization using a q-rung orthopair fuzzy Einstein based WASPAS approach. Journal of Cleaner Production, 347, 131239.
 
Deveci, M., Pamucar, D., Cali, U., Kantar, E., Kolle, K., Tande, J.O. (2022c). Hybrid q-rung orthopair fuzzy sets based CoCoSo model for floating offshore wind farm site selection in Norway. CSEE Journal of Power and Energy Systems, 8(5), 1261–1280.
 
Dincer, H., Yuksel, S., Mikhaylov, A., Barykin, S.E., Aksoy, T., Hacioglu, U. (2022). Analysis of environmental priorities for green project investments using an integrated q-rung orthopair fuzzy modeling. IEEE Access, 10, 50996–51007.
 
Du, W.S. (2018). Minkowski-type distance measures for generalized orthopair fuzzy sets. International Journal of Intelligent Systems, 33, 802–817.
 
Ecer, F. (2021). A consolidated MCDM framework for performance assessment of battery electric vehicles based on ranking strategies. Renewable & Sustainable Energy Reviews, 143, 110916.
 
Ecer, F. (2022). An extended MAIRCA method using intuitionistic fuzzy sets for coronavirus vaccine selection in the age of COVID-19. Neural Computing & Applications, 34(7), 5603–5623.
 
Ecer, F., Boyukaslan, A., Zolfani, S.H. (2022). Evaluation of cryptocurrencies for investment decisions in the era of Industry 4.0: a Borda count-based intuitionistic fuzzy set extensions EDAS-MAIRCA-MARCOS multi-criteria methodology. Axioms, 11(8), 404.
 
Erdogan, M. (2022). Assessing farmers’ perception to agriculture 4.0 technologies: a new interval-valued spherical fuzzy sets based approach. International Journal of Intelligent Systems, 37(2), 1751–1801.
 
Fan, J.P., Zhou, W., Wu, E.Q. (2022). A new method of conflicting evidence management based on non-extensive entropy and Lance distance in uncertain scenarios. Journal of Intelligent & Fuzzy Systems, 42, 6117–6129.
 
Gao, H., Lu, M., Wei, G.W., Wei, Y. (2018). Some novel Pythagorean fuzzy interaction aggregation operators in multiple attribute decision making. Fundamenta Informaticae, 159(4), 385–428.
 
Gigovic, L.J., Pamucar, D., Bajic, Z., Milicevic, M. (2016). The combination of expert judgment and GIS-MAIRCA analysis for the selection of sites for ammunition depots. Sustainability, 8(4), 372.
 
Gong, J.W., Li, Q., Yin, L.S., Liu, H.C. (2020). Undergraduate teaching audit and evaluation using an extended MABAC method under q-rung orthopair fuzzy environment. International Journal of Intelligent Systems, 35(12), 1912–1933.
 
Gul, M., Ak, M.F. (2020). Assessment of occupational risks from human health and environmental perspectives: a new integrated approach and its application using fuzzy BWM and fuzzy MAIRCA. Stochastic Environmental Research and Risk Assessment, 34(8), 1231–1262.
 
Guo, X., Xu, Z. (2016). Novel basic operational laws for linguistic terms, hesitant fuzzy linguistic term sets and probabilistic linguistic term sets. Information Sciences, 372, 407–427.
 
Hadian, S., Tabarestani, E.S., Pham, Q.B. (2022). Multi attributive ideal-real comparative analysis (MAIRCA) method for evaluating flood susceptibility in a temperate Mediterranean climate. Hydrological Sciences Journal, 67(3), 401–418.
 
Hashemkhani Zolfani, S., Ecer, F., Pamucar, D., Raslanas, S. (2020). Neighborhood selection for a newcomer via a novel BWM-based revised MAIRCA integrated model: a case from the Coquimbo-La Serena conurbation, Chile. International Journal of Strategic Property Management, 24(2), 102–118.
 
He, Y.D., He, Z., Huang, H. (2017). Decision making with the generalized intuitionistic fuzzy power interation averaging operators. Soft Computing, 21(5), 1129–1144.
 
Khan, M.J., Ali, M.I., Kumam, P., Kumam, W., Al-Kenani, A.N. (2021a). q-Rungorthopair fuzzy modified dissimilarity measure based robust VIKOR method and its applications in mass vaccination campaigns in the context of COVID-19. IEEE Access, 9, 93497–93515.
 
Khan, M.J., Kumam, P., Alreshidi, N.A., Kumam, W. (2021b). Improved cosine and cotangent function-based similarity measures for q-rung orthopair fuzzy sets and TOPSIS method. Complex & Intelligent Systems, 7(5), 2679–2696.
 
Krishankumar, R., Ravichandran, K.S., Kar, S., Cavallaro, F., Zavadskas, E.K. (2019). Scientific decision framework for evaluation of renewable energy sources under q-rung orthopair fuzzy set with partially known weight information. Sustainability, 11(15), 4202.
 
Krishankumar, R., Nimmagadda, S.S., Rani, P., Mishra, A.R., Ravichandran, K.S., Gandomi, A.H. (2021). Solving renewable energy source selection problems using a q-rung orthopair fuzzy-based integrated decision-making approach. Journal of Cleaner Production, 279, 123329.
 
Lance, G.N., Williams, W.T. (1966). Computer programs for hierarchical polythetic classification (“similarity analyses”). Computer Journal, 9(1), 60–64.
 
Li, Q., Chen, Q.Y., Liu, Z., Liu, H.C. (2021). Public transport customer satisfaction evaluation using an extended thermodynamic method: a case study of Shanghai, China. Soft Computing, 25(16), 10901–10914.
 
Liang, D.C., Tang, W.T., Fu, Y.Y. (2023). Sustainable modern agricultural technology assessment by a multistakeholder transdisciplinary approach. IEEE Transactions on Engineering Management, 70(3), 1061–1075. https://doi.org/10.1109/TEM.2021.3097333.
 
Liao, H.C., Zhang, H.R., Zhang, C., Wu, X.L., Mardani, A., Al-Barakati, A. (2020). A q-rung orthopair fuzzy GLDS method for investment evaluation of BE angel capital in China. Technological and Economic Development of Economy, 26(1), 103–134.
 
Liu, C., Rani, P., Pachori, K. (2022). Sustainable circular supplier selection and evaluation in the manufacturing sector using Pythagorean fuzzy EDAS approach. Journal of Enterprise Information Management, 35(4/5), 1040–1066.
 
Liu, L., Wu, J., Wei, G.W., Wei, C., Wang, J., Wei, Y. (2020). Entropy-based GLDS method for social capital selection of a PPP project with q-rung orthopair fuzzy information. Entropy, 22(4), 414.
 
Liu, P.D., Liu, J.L. (2018). Some q-rung orhtopair fuzzy Bonferroni mean operators and their application to multi-attribute group decision-making. International Journal of Intelligent Systems, 33(2), 315–347.
 
Liu, P.D., Wang, P. (2018). Some q-rung orthopair fuzzy aggregation operators and their applications to multiple-attribute decision making. International Journal of Intelligent Systems, 33(2), 259–280.
 
Liu, Z.M., Li, L., Zhao, X.L., Sha, L.B., Wang, D., Wang, X.Y., Liu, P.D. (2020). Selecting the optimal green agricultural products supplier: a novel approach based on GBWM and PROMETHEE II. Sustainability, 12(17), 6730.
 
Liu, Z.M., Wang, X.Y., Sun, N.N., Li, L., Wang, D., Liu, P.D. (2021). FMEA using the normalized projection-based TODIM-PROMETHEE II model for blood transfusion. International Journal of Fuzzy Systems, 23(6), 1680–1696.
 
Long, Y.L., Liao, H.C. (2021). A social participatory allocation network method with partial relations of alternatives and its application in sustainable food supply chain selection. Applied Soft Computing, 109, 107550.
 
Manupati, V.K., Ramkumar, M., Baba, V., Agarwal, A. (2021). Selection of the best healthcare waste disposal techniques during and post COVID-19 pandemic era. Journal of Cleaner Production, 281, 125175.
 
Mestanza, J.G., Bakhat, R. (2021). A fuzzy AHP-MAIRCA model for over tourism assessment: the case of Malaga province. Sustainability, 13(11), 6394.
 
Mishra, A.R., Rani, P. (2021). A q-rung orthopair fuzzy ARAS method based on entropy and discrimination measures: an application of sustainable recycling partner selection. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-021-03549-3.
 
Mishra, A.R., Rani, P., Pamucar, D., Hezam, I.M., Saha, A. (2022). Entropy and discrimination measures based q-rung orthopair fuzzy MULTIMOORA framework for selecting solid waste disposal method. Environmental Science and Pollution Research, 30, 12988–13011. https://doi.org/10.1007/s11356-022-22734-1.
 
Pamucar, D., Vasin, L., Lukovax, L. (2014). Selection of railway level crossings for investing in security equipment using hybrid DEMATEL-MAIRCA model. In: XVI International Scientific-Expert Conference on Railway, Railcon, pp. 89–92.
 
Pamucar, D., Gigovic, L., Bajic, Z., Janosevic, M. (2017a). Location selection for wind farms using GIS multi-criteria hybrid model: an approach based on fuzzy and rough numbers. Sustainability, 9(8), 1315.
 
Pamucar, D., Mihajlovic, M., Obradovic, R., Atanaskovic, P. (2017b). Novel approach to group multi-criteria decision making based on interval rough numbers: hybrid DEMATEL-ANP-MAIRCA model. Expert Systems with Applications, 88, 58–80.
 
Pamucar, D., Schitea, D., Eriskin, L., Iordache, M., Iordache, I., (2021). Developing a novel fuzzy neutrosophic numbers based decision making analysis for prioritizing the energy storage technologies. International Journal of Hydrogen Energy, 45(43), 23027–23074.
 
Peng, X.D., Luo, Z.G. (2021). A review of q-rung orthopair fuzzy information: bibliometrics and future directions. Artificial Intelligence Review, 54(5), 3361–3430.
 
Pinar, A., Boran, F.E. (2020). A q-rung orthopair fuzzy multi-criteria group decision making method for supplier selection based on a novel distance measure. International Journal of Machnine Learning and Cybernetics, 11(8), 1749–1780.
 
Pinar, A., Rouyendegh, B.D., Ozdemir, Y.S. (2021). q-rung orthopair fuzzy TOPSIS method for green supplier selection problem. Sustainability, 13(2), 985.
 
Riaz, M., Farid, H.M.A., Shakeel, H.M., Almalki, Y. (2022). Modernizing energy efficiency improvement with q-rung orthopair fuzzy MULTIMOORA approach. IEEE Access, 10, 74931–74947.
 
Saha, A., Ecer, F., Chatterjee, P., Senapati, T., Zavadskas, E.K. (2022a). q-rung orthopair fuzzy improved power weighted operators for solving group decision-making issues. Informatica, 33(3), 593–621.
 
Saha, A., Mishra, A.R., Rani, P., Hezam, I.M., Cavallaro, F. (2022b). A q-rung orthopair fuzzy FUCOM double normalization-based multi-aggregation method for healthcare waste treatment method selection. Sustainability, 14(7), 4171.
 
Sun, C., Sun, J.F., Alrasheedi, M., Saeidi, P., Mishra, A.R., Rani, P. (2021). A new extended VIKOR approach using q-rung orthopair fuzzy sets for sustainable enterprise risk management assessment in manufacturing small and medium-sized enterprises. International Journal of Fuzzy Systems, 23(5), 1347–1369.
 
Trung, N.Q., Thanh, N.V., Tinh, N.V., Husain, S.T. (2022). Fuzzy decision model: evaluating and selecting open banking business partners. CMC-Computers Materials & Continua, 72(3), 4557–4570.
 
Wang, H.L. (2021). T-spherical fuzzy rough interactive power Heronian mean aggregation operators for multiple attribute group decision-making. Symmetry, 13(12), 2422.
 
Wang, H.L., Ullah, K. (2022). T-spherical uncertain linguistic MARCOS method based on generalized distance and Heronian mean for multi-attribute group decision-making with unknown weight information. Complex IntellSyst. https://doi.org/10.1007/s40747-022-00862-y.
 
Wang, J., Wei, G.W., Wei, C., Wei, Y. (2020a). MABAC method for multiple attribute group decision making under q-rung orthopair fuzzy environment. Defence Technology, 16, 208–216.
 
Wang, J., Wei, G.W., Wei, C., Wu, J. (2020b). Maximizing deviation method for multiple attribute decision making under q-rung orthopair fuzzy environment. Defence Technology, 16, 1073–1087.
 
Wang, R., Li, Y.L. (2018). A novel approach for green supplier selection under a q-rung orthopair fuzzy environment. Symmetry, 10(12), 687.
 
Wang, Y.M. (1998). Using the method of maximizing deviations to make decision for multi-indices. Journal of System Engineering and Electronics, 7, 24–26.
 
Wei, G.W., Gao, H., Wei, Y. (2018). Some q-rung orthopair fuzzy Heronian mean operators in multiple attribute decision making. International Journal of Intelligent Systems, 33, 1426–1458.
 
Wei, G.W., Wei, C., Wang, J., Gao, H., Wei, Y. (2019). Some q-rung orthopair fuzzy Maclaurin symmetric mean operators and their applications to potential evaluation of emerging technology commercialization. International Journal of Intelligent Systems, 34, 50–81.
 
Xiao, L.M., Huang, G.Q., Pedrycz, W., Pamucar, D., Martinez, L., Zhang, G.B. (2022). A q-rung orthopair fuzzy decision-making model with new score function and best-worst method for manufacturer selection. Information Sciences, 608, 153–177.
 
Xing, Y.P., Zhang, R.T., Wang, J., Bai, K.Y., Xue, J. (2020). A new multi-criteria group decision-making approach based on q-rung orthopair fuzzy interaction Hamy mean operators. Neural Computing & Applications, 32(11), 7465–7488.
 
Yager, R. (2014). Pythagorean membership grades in multicriteria decision making. IEEE Transactions on Fuzzy Systems, 22(4), 958–965.
 
Yager, R. (2017). Generalized orthopair fuzzy sets. IEEE Transactions on Fuzzy Systems, 25(5), 1222–1230.
 
Yang, Z.Y., Ouyang, T.X., Fu, X.L., Peng, X.D. (2020). A decision-making algorithm for online shopping using deep learning-based opinion pairs mining and q-rung orthopair fuzzy interaction Heronian mean operators. International Journal of Intelligent Systems, 35(5), 783–825.
 
Yang, Z.L., Garg, H., Li, J.Q., Srivastava, G., Cao, Z.H. (2021). Investigation of multiple heterogeneous relationships using a q-rung orthopair fuzzy multi-criteria decision algorithm. Neural Computing and Applications, 33, 10771–10786.
 
Ye, A.H., Zhang, R.T., Wu, P., Xing, Y.P. (2021). q-rung orthopair fuzzy TOPSIS method and the application to information service quality evaluation in online health community. Journal of Intelligent & Fuzzy Systems, 41(2), 3697–3714.
 
Zadeh, L.A. (1965). Fuzzy sets. Information & Control, 8, 338–353.
 
Zhang, C., Liao, H.C., Luo, L., Xu, Z.S. (2021a). Low-carbon tourism destination selection by a thermodynamic feature-based method. Journal of the Operational Research Society, 73(8), 1692–1707.
 
Zhang, R.T., Zhao, B.T., Xing, Y.P., Bai, K.Y. (2021b). A novel multicriteria decision-making approach with unknown weight information under q-rung orthopair fuzzy environment. International Journal of Intelligent Systems, 36(12), 7309–7339.
 
Zhu, G.N., Ma, J., Hu, J. (2021). Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers. International Journal of Intelligent Systems, 36(10), 6032–6065.

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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© 2024 Vilnius University
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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