Arena, S., Florian, E., Zennaro, I., Orrù, P., & Sgarbossa, F. (2021). A novel decision support system for managing predictive maintenance strategies based on machine learning approaches. Safety Science. https://doi.org/10.1016/j.ssci.2021.105529
Boonkanit, P., & Suthiluck, K. (2023). Developing a Decision-Making Support System for a Smart Construction and Demolition Waste Transition to a Circular Economy. Sustainability. https://doi.org/10.3390/su15129672
Canbulut, G. (2026). A Novel Approach for Multi-Criteria Decision-Making Problem with Interval Valued Fuzzy Pythagorean Number Using CRITIC-MARCOS Methods. Journal of Intelligent & Fuzzy Systems, 50, 2601 - 2623. https://doi.org/10.1177/18758967261427575
Dabić-Miletić, S., & Simic, V. (2023). Smart and Sustainable Waste Tire Management: Decision-Making Challenges and Future Directions. Decision Making Advances. https://doi.org/10.31181/v120232
Dhouib, D. (2013). An extension of MACBETH method for a fuzzy environment to analyze alternatives in reverse logistics for automobile tire wastes. Omega-international Journal of Management Science, 42, 25-32. https://doi.org/10.1016/j.omega.2013.02.003
Djenadic, S., Tanasijević, M., Jovancic, P. D., Ignjatović, D., Petrović, D., & Bugarić, U. (2022). Risk Evaluation: Brief Review and Innovation Model Based on Fuzzy Logic and MCDM. Mathematics. https://doi.org/10.3390/math10050811
Erozan, I. (2019). A fuzzy decision support system for managing maintenance activities of critical components in manufacturing systems. Journal of Manufacturing Systems. https://doi.org/10.1016/j.jmsy.2019.06.002
Giel, R., & Kierzkowski, A. (2021). A Fuzzy Multi-Criteria Model for Municipal Waste Treatment Systems Evaluation including Energy Recovery. Energies. https://doi.org/10.3390/en15010031
Ikram, S. T., Mohanraj, V., Ramachandran, S., & Balakrishnan, A. (2023). An Intelligent Waste Management Application Using IoT and a Genetic Algorithm–Fuzzy Inference System. Applied Sciences. https://doi.org/10.3390/app13063943
Kokkinos, K., Lakioti, E., Moustakas, K., Tsanaktsidis, C., & Karayannis, V. (2023). Sustainable Medical Waste Management Using an Intuitionistic Fuzzy-Based Decision Support System. Sustainability. https://doi.org/10.3390/su16010298
Mamdani, E. H., & Assilian, S. (1975). An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, 7(1), 1-13.
Medina, G. C. A., Rosas Paredes, K., Zúñiga Carnero, M., & Sulla-Torres, J. (2022). Diagnostics in Tire Retreading Based on Classification with Fuzzy Inference System. Applied Sciences. https://doi.org/10.3390/app12199955
Pan, N.-H., Chang, H.-C., & Chen, K.-Y. (2025). A Hybrid AI-Fuzzy Decision Support Framework for UAV-Based Durability Assessment of Civil Infrastructure. IEEE Access, 13, 186408-186423. https://doi.org/10.1109/access.2025.3626054
Phadnis, A., Satish, D. A., Dharane, V., Hudnurka, M., & Ambekar, S. (2025). A Sustainable Approach to Waste Management of Tyres: Using Artificial Intelligence for Enhanced Accuracy. Australasian Accounting, Business and Finance Journal. https://doi.org/10.14453/aabfj.v19i1.02
Sazonova, E., Сметанина, О., & Yusupova, N. (2022). Models and methods of information support in the management of the maintenance and repair of equipment based on artificial intelligence technologies. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3996236
Schenck, C. J., Blaauw, P. F., & Viljoen, J. M. (2023). The role of informal actors in the circular economy of waste tires. Journal of Cleaner Production, 387, 135889.
Sebola, M., Mativenga, P. T., & Pretorius, J. H. C. (2018). A comparative study of the South African and European tire recycling industries. Waste Management & Research, 36(10), 938-947.
Ullah, K., Ahmad, Z., Rak, E., & Jafari, S. (2025). Multi-experts decision support system for recycling of waste material using some circular pythagorean fuzzy Muirhead means. Scientific Reports, 15. https://doi.org/10.1038/s41598-025-18521-w
United States Tire Manufacturers Association (USTMA). (2020). 2020 Scrap Tire Management Report. Washington, DC: USTMA.
World Business Council for Sustainable Development (WBCSD). (2019). Tire Industry Project: Recycling and Recovery. Geneva: WBCSD.
Yu, H., Chen, Y., Wu, Q., Zhang, L., Zhang, Z., Zhang, J.-H., Miljković, M., & Oeser, M. (2020). Decision support for selecting optimal method of recycling waste tire rubber into wax-based warm mix asphalt based on fuzzy comprehensive evaluation. Journal of Cleaner Production, 265, 121781. https://doi.org/10.1016/j.jclepro.2020.121781
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.
