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A Novel Entropy Measure with its Application to the COPRAS Method in Complex Spherical Fuzzy Environment
Volume 34, Issue 4 (2023), pp. 679–711
Ebru Aydoğdu ORCID icon link to view author Ebru Aydoğdu details   Başak Aldemir ORCID icon link to view author Başak Aldemir details   Elif Güner ORCID icon link to view author Elif Güner details   Halis Aygün ORCID icon link to view author Halis Aygün details  

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https://doi.org/10.15388/23-INFOR539
Pub. online: 20 November 2023      Type: Research Article      Open accessOpen Access

Received
1 October 2022
Accepted
1 November 2023
Published
20 November 2023

Abstract

A complex spherical fuzzy set (CSFS) is a generalization of the spherical fuzzy set (SFS) to express the two-dimensional ambiguous information in which the range of positive, neutral and negative degrees occurs in the complex plane with the unit disk. Considering the vital importance of the concept of CSFSs which is gaining massive attention in the research area of two-dimensional uncertain information, we aim to establish a novel methodology for multi-criteria group decision-making (MCGDM). This methodology allows us to calculate both the weights of the decision-makers (DMs) and the weights of the criteria objectively. For this goal, we first introduce a new entropy measure function that measures the fuzziness degree associated with a CSFS to compute the unknown criteria weights in this methodology. Then, we present an innovative Complex Proportional Assessment (COPRAS) method based on the proposed entropy measure in the complex spherical fuzzy environment. Besides, we solve a strategic supplier selection problem which is very important to maximize the efficiency of the trading companies. Finally, we present some comparative analyses with some existing methods in different set theories, including the entropy measures, to show the feasibility and usefulness of the proposed method in the decision-making process.

References

 
Akram, M., Bashir, A., Garg, H. (2020). Decision-making model under complex picture fuzzy Hamacher aggregation operators. Computational and Applied Mathematics, 39(3), 1–38.
 
Akram, M., Kahraman, C., Zahid, K. (2021a). Extension of TOPSIS model to the decision-making under complex spherical fuzzy information. Soft Computing, 25, 10771–10795.
 
Akram, M., Al-Kenani, A.N., Shabir, M. (2021b). Enhancing ELECTRE I method with complex spherical fuzzy information. International Journal of Computational Intelligence Systems, 14(1), 1–31.
 
Akram, M., Kahraman, C., Zahid, K. (2021c). Group decision-making based on complex spherical fuzzy VIKOR approach. Knowledge-Based Systems, 216, 106793.
 
Akram, M., Khan, A., Alcantud, J., Santos-García, G. (2021d). A hybrid decision-making framework under complex spherical fuzzy prioritized weighted aggregation operators. Expert Systems, 38(6), e12712.
 
Aldemir, B., Güner, E., Aydoğdu, E., Aygün, H. (2021). Complex spherical fuzzy TOPSIS method with Dombi aggregation operators. In: 1st International Symposium on Recent Advances in Fundamental and Applied Sciences. Ataturk University Publications.
 
Ali, Z., Mahmood, T., Yang, M. (2020). TOPSIS method based on complex spherical fuzzy sets with Bonferroni mean operators. Mathematics, 8(10), 1739–1760.
 
Alimardani, M., Hashemkhani Zolfani, S., Aghdaie, M.H., Tamošaitienė, J. (2013). A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment. Technological and Economic Development of Economy, 19(3), 533–548.
 
Alkan, Ö., Albayrak, Ö.K. (2020). Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA. Renewable Energy, 162, 712–726.
 
Alipour, M., Hafezi, R., Rani, P., Hafezi, M., Mardani, A. (2021). A new Pythagorean fuzzy-based decision-making method through entropy measure for fuel cell and hydrogen components supplier selection. Energy, 234, 121208.
 
Alkouri, A.U.M., Salleh, A.R. (2013). Complex Atanassov’s intuitionistic fuzzy relation. Abstract and Applied Analysis, 2013, 287382.
 
Anser, M.K., Mohsin, M., Abbas, Q., Chaudhry, I.S. (2020). Assessing the integration of solar power projects: SWOT-based AHP–F-TOPSIS case study of Turkey. Environmental Science and Pollution Research, 27(25), 31737–31749.
 
Atanassov, K. (2003). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96.
 
Aydoğdu, A., Gül, S. (2020). A novel entropy proposition for spherical fuzzy sets and its application in multiple attribute decision-making. International Journal of Intelligent Systems, 35(9), 1354–1374.
 
Aydoğdu, A., Gül, S. (2022). New entropy propositions for interval-valued spherical fuzzy sets and their usage in an extension of ARAS (ARAS-IVSFS). Expert Systems, 39(4), e12898.
 
Aydoğdu, E., Güner, E., Aldemir, B., Aygün, H. (2023). Complex spherical fuzzy TOPSIS based on entropy. Expert Systems with Applications, 215, 119331.
 
Azam, M., Ali Khan, M.S., Yang, S. (2022). A decision-making approach for the evaluation of information security management under complex intuitionistic fuzzy set environment. Journal of Mathematics, 2022, 9704466.
 
Balali, A., Valipour, A., Edwards, R., Moehler, R. (2021). Ranking effective risks on human resources threats in natural gas supply projects using ANP-COPRAS method: case study of Shiraz. Reliability Engineering and System Safety, 208, 107442.
 
Bozanic, D., Tešić, D., Milić, A. (2020). Multicriteria decision making model with Z-numbers based on FUCOM and MABAC model. Decision Making: Applications in Management and Engineering, 3(2), 19–36.
 
Brauers, W.K., Zavadskas, E.K. (2006). The MOORA method and its application to privatization in a transition economy. Control and Cybernetics, 35(2), 445–469.
 
Bhutta, K.S., Huq, F. (2002). Supplier selection problem: a comparison of the total cost of ownership and analytic hierarchy process approaches. Supply Chain Management, 7(3), 126–135.
 
Buyukozkan, G., Gocer, F. (2019). A novel approach integrating AHP and COPRAS under Pythagorean fuzzy sets for digital supply chain partner selection. IEEE Transactions on Engineering Management, 68(5), 1486–1503.
 
Chaurasiya, R., Jain, D. (2022). Pythagorean fuzzy entropy measure-based complex proportional assessment technique for solving multi-criteria healthcare waste treatment problem. Granular Computing, 7, 917–930.
 
Chen, S.M. (1988). A new approach to handling fuzzy decision-making problems. IEEE Transactions on Systems, Man, and Cybernetics, 18(6), 1012–1016.
 
Cuong, B. (2013). Picture fuzzy sets-first results. Seminar on Neuro–Fuzzy Systems with Applications. Institute of Mathematics, Hanoi.
 
De Luca, A., Termini, S. (1972). A definition of a nonprobabilistic entropy in the setting of fuzzy sets theory. Information and Control, 20(4), 301–312.
 
De Luca, A., Termini, S. (1977). On the convergence of entropy measures of a fuzzy set. Kybernetes, 6(3), 219–227.
 
Diakoulaki, D., Mavrotas, G., Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: the CRITIC method. Computers and Operations Research, 22(7), 763–770.
 
Dorfeshan, Y., Mousavi, S.M. (2019). A group TOPSIS-COPRAS methodology with Pythagorean fuzzy sets considering weights of experts for project critical path problem. Journal of Intelligent and Fuzzy Systems, 36(2), 1375–1387.
 
Ecer, F. (2014). A hybrid banking websites quality evaluation model using AHP and COPRAS-G: a Turkey case. Technological and Economic Development of Economy, 20(4), 758–782.
 
Fan, J., Xie, W. (1999). Distance measure and induced fuzzy entropy. Fuzzy Sets and Systems, 104(2), 305–314.
 
Gupta, H., Barua, M.K. (2017). Supplier selection among SMEs on the basis of their green innovation ability using BWM and fuzzy TOPSIS. Journal of Cleaner Production, 152, 242–258.
 
Gül, S., Aydoğdu, A. (2021). Novel entropy measure definitions and their uses in a modified combinative distance-based assessment (CODAS) method under picture fuzzy environment. Informatica, 32(4), 759–794.
 
Güner, E., Aygün, H. (2020). Generalized spherical fuzzy Einstein aggregation operators: application to multi-criteria group decision-making problems. Conference Proceedings of Science and Technology, 3(2), 227–235.
 
Güner, E., Aygün, H. (2022). Spherical fuzzy soft sets: theory and aggregation operator with its applications. Iranian Journal of Fuzzy Systems, 19(2), 83–97.
 
Güner, E., Aldemir, B., Aydoğdu, E., Aygün, H. (2022). Spherical fuzzy sets: AHP-COPRAS method based on Hamacher aggregation operator. Studies on Scientific Developments in Geometry, Algebra, and Applied Mathematics.
 
Hung, W., Yang, M. (2006). Fuzzy entropy on intuitionistic fuzzy sets. International Journal of Intelligent Systems, 21(4), 443–451.
 
Hwang, C.-L., Yoon, K. (1981). Methods for multiple attribute decision making. In: Multiple Attribute Decision Making, Lecture Notes in Economics and Mathematical Systems, Vol. 186. Springer, Berlin, Heidelberg, pp. 58–191.
 
Igoulalene, I., Benyoucef, L., Tiwari, M.K. (2015). Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem. Expert Systems with Applications, 42(7), 3342–3356.
 
Kahraman, C., Onar, S.C., Öztayşi, B., Şeker, Ş., Karaşan, A. (2020). Integration of fuzzy AHP with other fuzzy multicriteria methods: a state of the art survey. Journal of Multiple-Valued Logic and Soft Computing, 35(1–2), 61–92.
 
Keršuliene, V., Zavadskas, E.K., Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243–258.
 
Keshavarz-Ghorabaee, M. (2021). Assessment of distribution center locations using a multi-expert subjective–objective decision-making approach. Scientific Reports, 11(1), 1–19.
 
Keshavarz-Ghorabaee, M., Amiri, M., Kazimieras Zavadskas, E., Antuchevičienė, J. (2017). Assessment of third-party logistics providers using a CRITIC–WASPAS approach with interval type-2 fuzzy sets. Transport, 32(1), 66–78.
 
Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E.K., Turskis, Z., Antucheviciene, J. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Symmetry, 13(4), 525.
 
Kumari, R., Mishra, A.R. (2020). Multi-criteria COPRAS method based on parametric measures for intuitionistic fuzzy sets: application of green supplier selection. Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 44(4), 1645–1662.
 
Lu, J., Zhang, S., Wu, J., Wei, Y. (2021). COPRAS method for multiple attribute group decision making under picture fuzzy environment and their application to green supplier selection. Technological and Economic Development of Economy, 27(2), 369–385.
 
Mahmood, T., Kifayat, U., Khan, Q., Jan, N. (2018). An approach toward decision making and medical diagnosis problems using the concept of spherical fuzzy sets. Neural Computing and Applications, 31, 7041–7053.
 
Maji, P.K., Biswas, R., Roy, A.R. (2001). Fuzzy soft sets. Journal of Fuzzy Mathematics, 9(3), 589–602.
 
Mishra, A.R., Rani, P., Pandey, K., Mardani, A., Streimikis, J., Streimikiene, D., Alrasheedi, M. (2020). Novel multi-criteria intuitionistic fuzzy SWARA-COPRAS approach for sustainability evaluation of the bioenergy production process. Sustainability, 12(10), 4155.
 
Mishra, A.R., Saha, A., Rani, P., Hezam, I.M., Shrivastava, R., Smarandache, F. (2022). An integrated decision support framework using single-valued-MEREC-MULTIMOORA for low carbon tourism strategy assessment. IEEE Access, 10, 24411–24432.
 
Naeem, M., Qiyas, M., Botmart, T., Abdullah, S., Khan, N. (2022). Complex spherical fuzzy decision support system based on entropy measure and power operator. Journal of Function Spaces, 2022, 1–25.
 
Omerali, M., Kaya, T. (2022). Augmented reality application selection framework using spherical fuzzy COPRAS multi criteria decision making. Cogent Engineering, 9(1), 220610.
 
Opricovic, S. (1998). Multicriteria Optimization of Civil Engineering Systems. PhD Thesis, Faculty of Civil Engineering, Belgrade, 302 pp.
 
Pamucar, D., Stević, Ž., Sremac, S. (2018). A new model for determining weight coefficients of criteria in MCDM models: full consistency method (FUCOM). Symmetry, 10(9), 393.
 
Pamucar, D., Deveci, M., Canıtez, F., Lukovac, V. (2020). Selecting an airport ground access mode using novel fuzzy LBWA-WASPAS-H decision making model. Engineering Applications of Artificial Intelligence, 93, 103703.
 
Pamucar, D., Ecer, F., Deveci, M. (2021). Assessment of alternative fuel vehicles for sustainable road transportation of United States using integrated fuzzy FUCOM and neutrosophic fuzzy MARCOS methodology. Science of The Total Environment, 788, 147763.
 
Peng, X., Zhang, X., Luo, Z. (2020). Pythagorean fuzzy MCDM method based on CoCoSo and CRITIC with score function for 5G industry evaluation. Artificial Intelligence Review, 53(5), 3813–3847.
 
Rani, P., Mishra, A.R., Krishankumar, R., Mardani, A., Cavallaro, F., Soundarapandian Ravichandran, K., Balasubramanian, K. (2020a). Hesitant fuzzy SWARA-complex proportional assessment approach for sustainable supplier selection (HF-SWARA-COPRAS). Symmetry, 12(7), 1152.
 
Rani, P., Mishra, A.R., Mardani, A. (2020b). An extended Pythagorean fuzzy complex proportional assessment approach with new entropy and score function: application in pharmacological therapy selection for type 2 diabetes. Applied Soft Computing, 94, 106441.
 
Rani, P., Mishra, A.R., Saha, A., Hezam, I.M., Pamucar, D. (2022). Fermatean fuzzy Heronian mean operators and MEREC-based additive ratio assessment method: an application to food waste treatment technology selection. International Journal of Intelligent Systems, 37(3), 2612–2647.
 
Ramot, D., Milo, R., Friedman, M., Kandel, A. (2002). Complex fuzzy sets. IEEE Transactions on Fuzzy Systems, 10(2), 171–186.
 
Ramot, D., Friedman, M., Langholz, G., Kandel, A. (2003). Complex fuzzy logic. IEEE Transactions on Fuzzy Systems, 11(4), 450–461.
 
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57.
 
Saaty, T.L. (1980). How to make a decision: the analytic hierarchy process. European Journal of Operational Research, 48(1), 9–26.
 
Saaty, T.L. (1996). Decision with the Analytic Network Process. University of Pittsburgh, USA.
 
Sakthivel, G., Ilangkumaran, M., Gaikwad, A. (2015). A hybrid multi-criteria decision modeling approach for the best biodiesel blend selection based on ANP-TOPSIS analysis. Ain Shams Engineering Journal, 6(1), 239–256.
 
Schitea, D., Deveci, M., Bilgili, K. (2019). Hydrogen mobility roll-up site selection using intuitionistic fuzzy sets based WASPAS, COPRAS and EDAS. International Journal of Hydrogen Energy, 44(16), 8585–8600.
 
Thaoa, N., Smarandache, F. (2019). A new fuzzy entropy on Pythagorean fuzzy sets. Journal of Intelligent and Fuzzy Systems, 37, 1065–1074.
 
Torkayesh, A.E., Pamucar, D., Ecer, F., Chatterjee, P. (2021). An integrated BWM-LBWA-CoCoSo framework for evaluation of healthcare sectors in Eastern Europe. Socio-Economic Planning Sciences, 78, 101052.
 
Ullah, K., Mahmood, T., Ali, Z., Jan, N. (2020). On some distance measures of complex Pythagorean fuzzy sets and their applications in pattern recognition. Complex and Intelligent Systems, 6(1), 15–27.
 
Xuecheng, L. (1992). Entropy, distance measure and similarity measure of fuzzy sets and their relations. Fuzzy Sets and Systems, 52(3), 305–318.
 
Yager, R. (2013). Pythagorean fuzzy subsets. In: Proceedings of Joint IFSA World Congress and NAFIPS Annual Meeting, Edmonton, Canada.
 
Yang, Y.P.O., Shieh, H.M., Leu, J.D., Tzeng, G.H. (2008). A novel hybrid MCDM model combined with DEMATEL and ANP with applications. International Journal of Operations Research, 5(3), 160–168.
 
Yue, Z. (2013). An avoiding information loss approach to group decision making. Applied Mathematical Modelling, 37(1–2), 112–126.
 
Zadeh, L. (1965). Fuzzy sets. Information and Control, 8, 338–353.
 
Zahid, K., Akram, M., Kahraman, C. (2022). A new ELECTRE-based method for group decision-making with complex spherical fuzzy information. Knowledge-Based Systems, 243, 1–25.
 
Zavadskas, E.K., Kaklauskas, A., Sarka, V. (1994). The new method of multicriteria complex proportional assessment of projects. Technological and Economic Development of Economy, 1(3), 131–139.
 
Žižović, M., Pamucar, D. (2019). New model for determining criteria weights: Level Based Weight Assessment (LBWA) model. Decision Making: Applications in Management and Engineering, 2(2), 126–137.

Biographies

Aydoğdu Ebru
https://orcid.org/0000-0002-2777-8651
eaydogdu@dho.edu.tr

E. Aydoğdu is an assistant professor at Turkish National Defense University since 2023. She received her MSc degree in mathematics from the Institute of Natural and Applied Sciences of Atatürk University, in 2012, and PhD degree from Kocaeli University, in 2019. She worked as a research assistant at Kocaeli University between 2012–2023. Her research interests include fuzzy set theory, soft set theory, fixed point theory, metric space and multiple criteria decision analysis.

Aldemir Başak
https://orcid.org/0000-0002-9073-9364
baldemir@aku.edu.tr

B. Aldemir graduated from the Department of Mathematics at Kocaeli University in 2018. She received her master’s degree in mathematics in 2021. She is a PhD student at Kocaeli University. She has been working as a research assistant in the Department of Mathematics at Afyon Kocatepe University since 2021. Her areas of interest are general topology, metric spaces, fuzzy set theory, soft set theory, fixed point theory, decision-making theory, and image processing.

Güner Elif
https://orcid.org/0000-0002-6969-400X
elif.guner@kocaeli.edu.tr

E. Güner graduated from the Department of Mathematics at Kocaeli University in 2015. She received her master’s degree in Mathematics in 2018 and her PhD degree in 2023 from Kocaeli University. She has been working as a research assistant in the Department of Mathematics at Kocaeli University since 2016. Her area of interests are general topology, metric spaces, fuzzy set theory, soft set theory, fixed point theory and decision-making theory.

Aygün Halis
https://orcid.org/0000-0003-3263-3884
halis@kocaeli.edu.tr

H. Aygün graduated from the Department of Mathematics at Karadeniz Technical University in 1989. He received his master’s degree in mathematics from Karadeniz Technical University, in 1992, and his PhD degree from City University in London. He worked as a research assistant at Karadeniz Technical University and Kocaeli University between 1989–1993 and 1993–1998, respectively. He worked as an assistant professor and associate professor at Kocaeli University between 1998–2000 and 2000–2006, respectively. He has been a professor in the Department of Mathematics at Kocaeli University since 2006. His area of interests are general topology, fuzzy topology, metric spaces, fuzzy set theory, (fuzzy) soft set theory, lattice theory, fixed point theory and decision-making theory.


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Keywords
complex spherical fuzzy sets COPRAS entropy multi-criteria group decision-making supplier selection

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