An Interval-Valued Circular Intuitionistic Fuzzy MARCOS Method for Renewable Energy Source Selection

Vahideh Shahin; Moslem Alimohammadlou; Dragan Pamucar

doi:10.31181/sdmap31202645

Authors

Vahideh Shahin Department of Management, Faculty of Economics, Management and Social Sciences, Shiraz University, Shiraz, Iran Author https://orcid.org/0000-0002-9183-4283
Moslem Alimohammadlou Department of Management, Faculty of Economics, Management and Social Sciences, Shiraz University, Shiraz, Iran Author https://orcid.org/0000-0002-9463-7285
Dragan Pamucar 1) Széchenyi István University, Győr, Hungary; 2) Department of Applied Mathematical Science, College of Science and Technology, Korea University, Sejong 30019, Republic of Korea; 3) School of Engineering and Technology, Sunway University, Selangor, Malaysia Author https://orcid.org/0000-0001-8522-1942

DOI:

https://doi.org/10.31181/sdmap31202645

Keywords:

Interval-valued circular intuitionistic fuzzy sets, IVCIFSs, MARCOS, MCDM, Renewable energy sources

Abstract

The global shift toward renewable energy has heightened the demand for precise decision-making frameworks that can effectively handle uncertainty in complex, multi-criteria evaluations. Traditional approaches often fall short in capturing the nonlinear hesitation and interval-based uncertainty present in real-world assessments. To address this challenge, this study introduces a novel decision-making framework that integrates interval-valued circular intuitionistic fuzzy sets (IVCIFSs) with the Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) method. This hybrid approach effectively captures both interval-based uncertainty and nonlinear hesitation in expert judgments, making it particularly suitable for evaluating renewable energy sources (RES), where subjective assessments and conflicting criteria are common. To validate its practical utility, the framework was applied to a case study involving 10 RES alternatives across 7 criteria for a mid-sized Iranian food manufacturer. The analysis identified Economic Feasibility, Technical Viability, and Environmental Impact as critical criteria, with photovoltaic, biomass, and biodiesel emerging as the most favorable options. Comprehensive sensitivity and comparative analyses confirmed the model’s robustness across varying expert perspectives and its alignment with advanced multi-criteria decision-making (MCDM) methods. This study not only advances decision-making theory through the IVCIF-MARCOS integration but also offers a practical, adaptable tool for supporting effective energy transitions in uncertain and complex environments.

Downloads

Download data is not yet available.

References

Ionescu, S.-A., & Diaconita, V. (2023). Transforming financial decision-making: The interplay of AI, cloud computing and advanced data management technologies. International Journal of Computers Communications & Control, 18(6). https://doi.org/10.15837/ijccc.2023.6.5735

Więckowski, J., Wątróbski, J., & Sałabun, W. (2024). Toward robust decision-making under multiple evaluation scenarios with a novel fuzzy ranking approach: Green supplier selection study case. Artificial Intelligence Review, 58(1), 3. https://doi.org/10.1007/s10462-024-11006-8

Wiebe, K., Zurek, M., Lord, S., Brzezina, N., Gabrielyan, G., Libertini, J., Loch, A., Thapa-Parajuli, R., Vervoort, J., & Westhoek, H. (2018). Scenario development and foresight analysis: Exploring options to inform choices. Annual Review of Environment and Resources, 43(1), 545–570. https://doi.org/10.1146/annurev-environ-102017-030109

Bashan, V., Yucesan, M., Demirel, H., & Gul, M. (2025). Analyzing failures in wind-solar hybrid energy systems using a fuzzy-based BWM-MARCOS approach: Challenges and solutions. Arabian Journal for Science and Engineering. https://doi.org/10.1007/s13369-025-10054-8

Sahoo, S. K., Choudhury, B. B., & Dhal, P. R. (2024). A bibliometric analysis of material selection using MCDM methods: Trends and insights. Spectrum of Mechanical Engineering and Operational Research, 1(1), 189–205. https://doi.org/10.31181/smeor11202417

Khan, H. U., Abbas, M., Khan, F., Nazir, S., Binbusayyis, A., Alabdultif, A., & Taegkeun, W. (2024). Multi-criteria decision-making methods for the evaluation of the social internet of things for the potential of defining human behaviors. Computers in Human Behavior, 157, 108230. https://doi.org/10.1016/j.chb.2024.108230

Demir, G., Riaz, M., & Deveci, M. (2024). Wind farm site selection using geographic information system and fuzzy decision making model. Expert Systems with Applications, 255, 124772. https://doi.org/10.1016/j.eswa.2024.124772

Hezam, I. M., Ali, A. M., Sallam, K., Hameed, I. A., & Abdel-Basset, M. (2024). Digital twin and fuzzy framework for supply chain sustainability risk assessment and management in supplier selection. Scientific Reports, 14(1), 17718. https://doi.org/10.1038/s41598-024-67226-z

Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & Industrial Engineering, 140, 106231. https://doi.org/10.1016/j.cie.2019.106231

Salimian, S., Mousavi, S. M., & Antucheviciene, J. (2022). An interval-valued intuitionistic fuzzy model based on extended VIKOR and MARCOS for sustainable supplier selection in organ transplantation networks for healthcare devices. Sustainability, 14(7), 3795. https://doi.org/10.3390/su14073795

Mishra, A. R., Rani, P., Pamucar, D., & Saha, A. (2024). An integrated Pythagorean fuzzy fairly operator-based MARCOS method for solving the sustainable circular supplier selection problem. Annals of Operations Research, 342(1), 523–564. https://doi.org/10.1007/s10479-023-05453-9

Isik, Ö., Shabir, M., Demir, G., Puska, A., & Pamucar, D. (2025). A hybrid framework for assessing Pakistani commercial bank performance using multi-criteria decision-making. Financial Innovation, 11(1), 38. https://doi.org/10.1186/s40854-024-00728-x

Ecer, F., & Pamucar, D. (2021). MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare services. Applied Soft Computing, 104, 107199. https://doi.org/10.1016/j.asoc.2021.107199

Du, P. L., Chen, Z., Wang, Y., & Zhang, Z. Q. (2022). A hybrid group-making decision framework for regional distribution network outage loss assessment based on fuzzy best-worst and MARCOS methods. Sustainable Energy Grids & Networks, 31, 100734. https://doi.org/10.1016/j.segan.2022.100734

Bouraima, M. B., Tengecha, N. A., Stevic, Z., Simic, V., & Qiu, Y. J. (2024). An integrated fuzzy MCDM model for prioritizing strategies for successful implementation and operation of the bus rapid transit system. Annals of Operations Research, 342(1), 141–172. https://doi.org/10.1007/s10479-023-05183-y

Ghoushchi, S. J., Ab Rahman, M. N., Soltanzadeh, M., Rafique, M. Z., Hernadewita, Marangalo, F. Y., & Ismail, A. R. (2023). Assessing sustainable passenger transportation systems to address climate change based on MCDM methods in an uncertain environment. Sustainability, 15(4), 3558. https://doi.org/10.3390/su15043558

Aydin, M., Camliyurt, G., Gul, M., Sezer, S. I., Celik, E., & Akyuz, E. (2025). An interval type-2 fuzzy MARCOS modelling to assess performance effectiveness of survival craft on cargo ship. Ocean Engineering, 326, 120899. https://doi.org/10.1016/j.oceaneng.2025.120899

Younis, M., Ashraf, S., Abdullah, S., Shahid, T., & Gokul, K. C. (2025). Strategic MARCOS model for optimizing renewable energy investments under Pythagorean hesitant fuzzy assessments. Advances in Fuzzy Systems, 2025, 6193403. https://doi.org/10.1155/adfs/6193403

Taghipour, A., Padash, A., Etemadi, V., Khazaei, M., & Ebrahimi, S. (2024). Sustainable and circular hotels and the water-food-energy nexus: Integration of agrivoltaics, hydropower, solar cells, water reservoirs, and green roofs. Sustainability, 16(5), 1985. https://doi.org/10.3390/su16051985

Ahmad, Q. A., Ashraf, S., Iqbal, W., & Qiang, M. L. (2024). Enhanced decision technique for optimized crude oil pretreatment under disc spherical fuzzy Aczel Alsina aggregation information. Scientific Reports, 14(1), 15088. https://doi.org/10.1038/s41598-024-62036-9

Shang, N., Wang, H. F., & Fan, J. (2025). A robust large-scale multi-criteria decision algorithm for financial risk management with interval-valued picture fuzzy information. Symmetry, 17(1), 144. https://doi.org/10.3390/sym17010144

Stankovic, M., Stevic, Z., Das, D. K., Subotic, M., & Pamucar, D. (2020). A new fuzzy MARCOS method for road traffic risk analysis. Mathematics, 8(3), 457. https://doi.org/10.3390/math8030457

Mei, L. W., Feng, X. J., & Cavallaro, F. (2023). Evaluate and identify the competencies of the future workforce for digital technologies implementation in higher education. Journal of Innovation & Knowledge, 8(4), 100445. https://doi.org/10.1016/j.jik.2023.100445

Rani, P., Chen, S. M., & Mishra, A. R. (2024). Multi-attribute decision-making based on similarity measure between picture fuzzy sets and the MARCOS method. Information Sciences, 658, 119990. https://doi.org/10.1016/j.ins.2023.119990

Peng, X. D., Garg, H., & Luo, Z. G. (2023). When content-centric networking meets multi-criteria group decision-making: Optimal cache placement policy achieved by MARCOS with q-rung orthopair fuzzy set pair analysis. Engineering Applications of Artificial Intelligence, 123, 106231. https://doi.org/10.1016/j.engappai.2023.106231

Ali, J. (2021). A novel score function based CRITIC-MARCOS method with spherical fuzzy information. Computational & Applied Mathematics, 40(8), 280. https://doi.org/10.1007/s40314-021-01670-9

Mishra, A. R., Rani, P., Saeidi, P., Deveci, M., & Alrasheedi, A. F. (2024). Fermatean fuzzy score function and distance measure based group decision making framework for household waste recycling plant location selection. Scientific Reports, 14(1), 28106. https://doi.org/10.1038/s41598-024-78158-z

Kamber, E., & Baskak, M. (2024). Green logistics park location selection with circular intuitionistic fuzzy CODAS method: The case of Istanbul. Journal of Intelligent & Fuzzy Systems, 46(2), 4173–4189. https://doi.org/10.3233/JIFS-231843

Ashraf, S., Chohan, M. S., Muhammad, S., & Khan, F. (2023). Circular intuitionistic fuzzy TODIM approach for material selection for cryogenic storage tank for liquid nitrogen transportation. IEEE Access, 11, 98458–98468. https://doi.org/10.1109/ACCESS.2023.3312568

Otay, İ., Çevik Onar, S., Öztayşi, B., & Kahraman, C. (2023). A novel interval valued circular intuitionistic fuzzy AHP methodology: Application in digital transformation project selection. Information Sciences, 647, 119407. https://doi.org/10.1016/j.ins.2023.119407

Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X

Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—I. Information Sciences, 8(3), 199–249. https://doi.org/10.1016/0020-0255(75)90036-5

Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3

Jafarzadeh Ghoushchi, S., Shaffiee Haghshenas, S., Vahabzadeh, S., Shaffiee Haghshenas, S., Astarita, V., & Guido, G. (2025). Risk assessment of young driver behavior using an extended decision-making approach based on FMEA in uncertain environments. Neural Computing and Applications. https://doi.org/10.1007/s00521-025-11087-8

Yager, R. R. (2013). Pythagorean fuzzy subsets. *2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS)*. https://doi.org/10.1109/IFSA-NAFIPS.2013.6608375

Yager, R. R. (2017). Generalized Orthopair Fuzzy Sets. IEEE Transactions on Fuzzy Systems, 25(5), 1222–1230. https://doi.org/10.1109/TFUZZ.2016.2604005

Cuong, B. C., & Kreinovich, V. (2013). Picture fuzzy sets—a new concept for computational intelligence problems. 2013 Third World Congress on Information and Communication Technologies (WICT 2013). https://doi.org/10.1109/WICT.2013.7113099

Peng, J. J., Chen, X. G., Tan, H., Sun, J. Y., Long, Q. Q., & Jiang, L. L. (2024). A heterogeneous picture fuzzy SWARA-MARCOS evaluation framework based on a novel cross-entropy measure. International Journal of Systems Science, 55(8), 1528–1552. https://doi.org/10.1080/00207721.2024.2312881

Khalil, A. M., Li, S.-G., Garg, H., Li, H., & Ma, S. (2019). New operations on interval-valued picture fuzzy set, interval-valued picture fuzzy soft set and their applications. IEEE Access, 7, 51236–51253. https://doi.org/10.1109/ACCESS.2019.2910844

Kutlu Gündoğdu, F., & Kahraman, C. (2019). Spherical fuzzy sets and spherical fuzzy TOPSIS method. Journal of Intelligent & Fuzzy Systems, 36(1), 337–352. https://doi.org/10.3233/JIFS-181401

Atanassov, K. T., & Kahraman, C. (2020). Circular intuitionistic fuzzy sets. Journal of Intelligent & Fuzzy Systems, 39(5), 5981–5986. https://doi.org/10.3233/jifs-189072

Attia, E. A., & Uddin, M. S. (2024). Hybrid assessment for strengthening supply chain resilience and sustainability: A comprehensive analysis. Sustainability, 16(10), 4010. https://doi.org/10.3390/su16104010

Stević, Ž., Karamaşa, Ç., Demir, E., & Korucuk, S. (2025). Assessing sustainable production under circular economy context using a novel rough-fuzzy MCDM model: A case of the forestry industry in the Eastern Black Sea region. Journal of Enterprise Information Management, 38(1), 261–291. https://doi.org/10.1108/JEIM-10-2020-0419

Haseli, G., Ögel, I. Y., Ecer, F., & Hajiaghaei-Keshteli, M. (2023). Luxury in female technology (FemTech): Selection of smart jewelry for women through BCM-MARCOS group decision-making framework with fuzzy ZE-numbers. Technological Forecasting and Social Change, 196, 122870. https://doi.org/10.1016/j.techfore.2023.122870

Wang, N., Xu, Y., Puska, A., Stevic, Z., & Alrasheedi, A. F. (2023). Multi-criteria selection of electric delivery vehicles using fuzzy-rough methods. Sustainability, 15(21), 15541. https://doi.org/10.3390/su152115541

Gölcük, I., Durmaz, E. D., & Sahin, R. (2022). Interval type-2 fuzzy development of FUCOM and activity relationship charts along with MARCOS for facilities layout evaluation. Applied Soft Computing, 128, 109414. https://doi.org/10.1016/j.asoc.2022.109414

Akkus, D., & Testik, O. M. (2024). A novel method for weighting decision makers for failure mode and effect analysis under intuitionistic fuzzy environment. Quality and Reliability Engineering International, 40(4), 1566–1592. https://doi.org/10.1002/qre.3510

Saeed, M., Haq, R. S. U., Ahmed, S., Siddiqui, F., Mateen, N., Ahmed, K. A., Yi, J., & Pamucar, D. (2024). Sustainable selection of microwave absorbing materials: A green evaluation under interval-valued intuitionistic fuzzy environment. Cleaner Materials, 11, 100236. https://doi.org/10.1016/j.clema.2024.100236

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. https://doi.org/10.1016/j.scitotenv.2021.147763

Majumder, P., Das, A., Hezam, I. M., Alshamrani, A., & Aqlan, F. (2023). Integrating trapezoidal fuzzy best-worst method and single-valued neutrosophic fuzzy MARCOS for efficiency analysis of surface water treatment plants. Soft Computing. https://doi.org/10.1007/s00500-023-08532-y

Ecer, F., Tanriverdi, G., Yasar, M., & Görçün, Ö. (2025). Sustainable aviation fuel supplier evaluation for airlines through LOPCOW and MARCOS approaches with interval-valued fuzzy neutrosophic information. Journal of Air Transport Management, 123, 102705. https://doi.org/10.1016/j.jairtraman.2024.102705

Li, G., Geng, X. L., & Yuan, Y. (2023). The supplier performance evaluation of sports event service under the COVID-19 outbreak: A novel hesitant fuzzy MARCOS method. Journal of Intelligent & Fuzzy Systems, 45(3), 3965–3984. https://doi.org/10.3233/JIFS-230601

Zeng, S. Z., Ye, A. Q., Su, W. H., Chen, M. L., & Llopis-Albert, C. (2024). Site evaluation of subsea tunnels with sightseeing function based on dynamic complex MARCOS method. Technological Forecasting and Social Change, 199, 123041. https://doi.org/10.1016/j.techfore.2023.123041

Simic, V., Sousek, R., & Jovcic, S. (2020). Picture fuzzy MCDM approach for risk assessment of railway infrastructure. Mathematics, 8(12), 2259. https://doi.org/10.3390/math8122259

Rong, Y., & Yu, L. Y. (2024). An extended MARCOS approach and generalized Dombi aggregation operators-based group decision-making for emergency logistics suppliers selection utilizing q-rung picture fuzzy information. Granular Computing, 9(1), 22. https://doi.org/10.1007/s41066-023-00439-1

Mao, Q. H., Gao, Y. Q., & Fan, J. C. (2025). An investment decision framework for offshore CCUS project under interval-valued fermatean fuzzy environment. Environmental Technology, 46(7), 1112–1137. https://doi.org/10.1080/09593330.2024.2376291

Haseli, G., Deveci, M., Isik, M., Gokasar, I., Pamucar, D., & Hajiaghaei-Keshteli, M. (2024). Providing climate change resilient land-use transport projects with green finance using Z extended numbers based decision-making model. Expert Systems with Applications, 243, 122858. https://doi.org/10.1016/j.eswa.2023.122858

Majumder, P. (2023). An integrated trapezoidal fuzzy FUCOM with single-valued neutrosophic fuzzy MARCOS and GMDH method to determine the alternatives weight and its applications in efficiency analysis of water treatment plant. Expert Systems with Applications, 225, 120087. https://doi.org/10.1016/j.eswa.2023.120087

Stevic, Z., Karamasa, C., Demir, E., & Korucuk, S. (2021). Assessing sustainable production under circular economy context using a novel rough-fuzzy MCDM model: A case of the forestry industry in the Eastern Black Sea region. Journal of Enterprise Information Management. https://doi.org/10.1108/JEIM-10-2020-0419

Kaya, S. K. (2023). A novel two-phase group decision-making model for circular supplier selection under picture fuzzy environment. Environmental Science and Pollution Research, 30(12), 34135–34157. https://doi.org/10.1007/s11356-022-24486-4

Jayakumar, V., Kannan, J., Kausar, N., Deveci, M., & Wen, X. (2024). Multicriteria group decision making for prioritizing IoT risk factors with linear diophantine fuzzy sets and MARCOS method. Granular Computing, 9(3), 56. https://doi.org/10.1007/s41066-024-00480-8

Chen, T.-Y. (2023). Evolved distance measures for circular intuitionistic fuzzy sets and their exploitation in the technique for order preference by similarity to ideal solutions. Artificial Intelligence Review, 56(7), 7347–7401. https://doi.org/10.1007/s10462-022-10318-x

Selvaraj, J., & Majumdar, A. (2021). A new ranking method for interval-valued intuitionistic fuzzy numbers and its application in multi-criteria decision-making. Mathematics, 9(21), 2647. https://doi.org/10.3390/math9212647

Çakır, E., & Taş, M. A. (2023). Circular intuitionistic fuzzy decision making and its application. Expert Systems with Applications, 225, 120076. https://doi.org/10.1016/j.eswa.2023.120076

Du, W. S. (2021). Subtraction and division operations on intuitionistic fuzzy sets derived from the Hamming distance. Information Sciences, 571, 206–224. https://doi.org/10.1016/j.ins.2021.04.068

Ben Belgacem, S., Khatoon, G., & Alzuman, A. (2023). Role of renewable energy and financial innovation in environmental protection: Empirical evidence from UAE and Saudi Arabia. Sustainability, 15(11), 8684. https://doi.org/10.3390/su15118684

Lenarczyk, A., Jaskólski, M., & Bućko, P. (2022). The application of a multi-criteria decision-making for indication of directions of the development of renewable energy sources in the context of energy policy. Energies, 15(24), 9629. https://doi.org/10.3390/en15249629

Magableh, G. M., & Bazel, N. K. (2025). Exploring future renewable energy technologies using a developed model and a variety of MCDM approaches. Sustainability, 17(7), 3057. https://doi.org/10.3390/su17073057

Puška, A., Nedeljković, M., Dudić, B., Štilić, A., & Mittelman, A. (2024). Improving agricultural sustainability in Bosnia and Herzegovina through renewable energy integration. Economies, 12(8), 195. https://doi.org/10.3390/economies12080195

Dirma, V., Neverauskienė, L. O., Tvaronavičienė, M., Danilevičienė, I., & Tamošiūnienė, R. (2024). The impact of renewable energy development on economic growth. Energies, 17(24), 6328. https://doi.org/10.3390/en17246328

Segreto, M., Principe, L., Desormeaux, A., Torre, M., Tomassetti, L., Tratzi, P., Paolini, V., & Petracchini, F. (2020). Trends in social acceptance of renewable energy across Europe—A literature review. International Journal of Environmental Research and Public Health, 17(24), 9161. https://doi.org/10.3390/ijerph17249161

Chen, X. H., Tee, K., Elnahass, M., & Ahmed, R. (2023). Assessing the environmental impacts of renewable energy sources: A case study on air pollution and carbon emissions in China. Journal of Environmental Management, 345, 118525. https://doi.org/10.1016/j.jenvman.2023.118525

Moreno-Rocha, C. M., Nuñez-Alvarez, J. R., Rivera-Alvarado, J., Ruiz, A. G., & Buelvas-Sanchez, E. A. (2025). Multi-criteria evaluation and multi-method analysis for appropriately selecting renewable energy sources in Colombia. MethodsX, 14, 103248. https://doi.org/10.1016/j.mex.2025.103248

Firoozi, A. A., Hejazi, F., & Firoozi, A. A. (2024). Advancing wind energy efficiency: A systematic review of aerodynamic optimization in wind turbine blade design. Energies, 17(12), 2919. https://doi.org/10.3390/en17122919

Liczmańska-Kopcewicz, K., Pypłacz, P., & Wiśniewska, A. (2020). Resonance of investments in renewable energy sources in industrial enterprises in the food industry. Energies, 13(17), 4285. https://doi.org/10.3390/en13174285

Sharma, R. (2025). Can the human body be a source of energy harvesting?—Present and future prospective. IEEE Transactions on Human-Machine Systems. https://doi.org/10.1109/THMS.2025.3552662

Hasan, M., Hossain, S., Mofijur, M., Kabir, Z., Badruddin, I. A., Khan, T. Y., & Jassim, E. (2023). Harnessing solar power: A review of photovoltaic innovations, solar thermal systems, and the dawn of energy storage solutions. Energies, 16(18), 6456. https://doi.org/10.3390/en16186456

Vahidhosseini, S. M., Rashidi, S., Hsu, S.-H., Yan, W.-M., & Rashidi, A. (2024). Integration of solar thermal collectors and heat pumps with thermal energy storage systems for building energy demand reduction: A comprehensive review. Journal of Energy Storage, 95, 112568. https://doi.org/10.1016/j.est.2024.112568

Pavičić, J., Novak Mavar, K., Brkić, V., & Simon, K. (2022). Biogas and biomethane production and usage: Technology development, advantages and challenges in Europe. Energies, 15(8), 2940. https://doi.org/10.3390/en15082940

Kyriklidis, C., Koutouvou, A., Moustakas, K., Karayannis, V., & Tsanaktsidis, C. (2025). Artificial intelligence and nature-inspired techniques on optimal biodiesel production: A review—Recent trends. Energies, 18(4), 768. https://doi.org/10.3390/en18040768

González Fernández, L. A., Medellín Castillo, N. A., Sánchez Polo, M., Navarro Frómeta, A. E., & Vilasó Cadre, J. E. (2025). Algal-based carbonaceous materials for environmental remediation: Advances in wastewater treatment, carbon sequestration, and biofuel applications. Processes, 13(2), 556. https://doi.org/10.3390/pr13020556

Falfushynska, H. (2024). Advancements and prospects in algal biofuel production: A comprehensive review. Phycology, 4(4), 548–575. https://doi.org/10.3390/phycology4040030

Kumar, P. V. A., Patnaik, L., Bharati, K., Venkatesh, V. S. S., & Kumar, S. (2024). Investigating tool wear rate and surface quality of hardened tool steel: A fuzzy-MARCOS analysis and response surface methodology study. International Journal of Interactive Design and Manufacturing, 18(6), 4137–4158. https://doi.org/10.1007/s12008-024-01950-8

Li, J., Wu, T., Cheng, C., Li, J., & Zhou, K. (2024). A review of the research progress and application of key components in the hydrogen fuel cell system. Processes, 12(2), 249. https://doi.org/10.3390/pr12020249

Khalil, A., Attom, M., Khan, Z., Astillo, P. V., & El-Kadri, O. M. (2024). Recent advancements in geothermal energy piles performance and design. Energies, 17(14), 3386. https://doi.org/10.3390/en17143386

Hezam, I. M., Mishra, A. K., Pamucar, D., Rani, P., & Mishra, A. R. (2024). Standard deviation and rank sum-based MARCOS model under intuitionistic fuzzy information for hospital site selection. Kybernetes, 53(10), 3727–3753. https://doi.org/10.1108/K-01-2023-0136

Chaurasiya, R., & Jain, D. (2023). A new algorithm on Pythagorean fuzzy-based multi-criteria decision-making and its application. Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 47(3), 871–886. https://doi.org/10.1007/s40998-023-00600-1

Jafarzadeh Ghoushchi, S., Shaffiee Haghshenas, S., Memarpour Ghiaci, A., Guido, G., & Vitale, A. (2023). Road safety assessment and risks prioritization using an integrated SWARA and MARCOS approach under spherical fuzzy environment. Neural Computing and Applications, 35(6), 4549–4567. https://doi.org/10.1007/s00521-022-07929-4

AlFadhli, M. S., Ayvaz, B., Kucukvar, M., Alkhereibi, A. H., Onat, N., & Al-Maadeed, S. (2025). A novel spherical fuzzy-based decision model for assessing data management maturity in governmental institutions. International Journal of Data Science and Analytics. https://doi.org/10.1007/s41060-024-00701-y

Kendall, M. G. (1938). A new measure of rank correlation. Biometrika, 30(1-2), 81–93. https://doi.org/10.1093/biomet/30.1-2.81