Fuzzy Multi-Criteria Decision-Making Method F-PSWCA: A Case Study on the Selection and Ranking of Criteria and New Technologies in Dialysis

Document Type : Research Paper

Authors

1 PhD candidate, Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.

2 Associate professor, Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.

Abstract

Selecting appropriate technologies in healthcare systems is a complex decision-making problem involving multiple, often conflicting criteria under uncertainty. In this paper, a novel fuzzy multi-criteria decision-making (MCDM) method, referred to as F-PSWCA, is proposed to enhance the criteria weighting process by incorporating historical performance trends within a fuzzy environment. The proposed method integrates fuzzy regression parameters, including slope, intercept, and coefficient of determination (R²), to capture both the magnitude and stability of criteria over time. Unlike conventional fuzzy MCDM approaches that rely solely on static expert judgments, F-PSWCA enables dynamic assessment of criteria importance while preserving uncertainty representation. The applicability of the proposed method is demonstrated through a real-world case study on the selection of dialysis water purification technologies, where multiple technical, economic, and operational criteria are considered. Comparative analysis with Fuzzy SAW, Fuzzy TOPSIS, and Fuzzy SECA is conducted to evaluate the robustness and consistency of the results. The findings indicate that while ranking similarities may occur across methods, F-PSWCA provides additional interpretive insights by distinguishing between temporally stable and unstable criteria. The results confirm the effectiveness of the proposed approach as a decision-support tool for technology selection in complex and evolving healthcare environments.

Keywords

Main Subjects


Alamroshan, F., La’li, M., & Yahyaei, M. (2022). The green-agile supplier selection problem for the medical devices: a hybrid fuzzy decision-making approach. Environmental Science and Pollution Research, 29(5), 6793–6811. https://doi.org/10.1007/s11356-021-14690-z.
Aldaghi, T., & Muzik, J. (2024). Multicriteria Decision-Making in Diabetes Management and Decision Support: Systematic Review. JMIR Medical Informatics, 12. https://doi.org/10.2196/47701.
Aliasgharzadeh, S., Ebrahimi-Mameghani, M., Mahdavi, R., Karimzadeh, H., Nikniaz, L., Tabrizi, J. S., & Pourali, F. (2022). Prioritizing population-based nutrition-related interventions to prevent and control hypertension in Iran: a multi-criteria decision-making approach. BMC Medical Research Methodology, 22(1). https://doi.org/10.1186/s12874-022-01761-z.
Ansari, M. T. J., Al-Zahrani, F. A., Pandey, D., & Agrawal, A. (2020). A fuzzy TOPSIS based analysis toward selection of effective security requirements engineering approach for trustworthy healthcare software development. BMC Medical Informatics and Decision Making, 20(1). https://doi.org/10.1186/s12911-020-01209-8.
Badida, P., Janakiraman, S., & Jayaprakash, J. (2023). Occupational health and safety risk assessment using a fuzzy multi-criteria approach in a hospital in Chennai, India. International Journal of Occupational Safety and Ergonomics, 29(3). https://doi.org/10.1080/10803548.2022.2109323.
Beheshtinia, M. A., Jafari Kahoo, S., & Fathi, M. (2023). Prioritizing healthcare waste disposal methods considering environmental health using an enhanced multi-criteria decision-making method. Environmental Pollutants and Bioavailability, 35(1). https://doi.org/10.1080/26395940.2023.2218568.
Chakraborty, S., Raut, R. D., Rofin, T. M., & Chakraborty, S. (2023). A comprehensive and systematic review of multi-criteria decision-making methods and applications in healthcare. In Healthcare Analytics (Vol. 4). https://doi.org/10.1016/j.health.2023.100232.
Gao, K., Liu, T., Rong, Y., Simic, V., Garg, H., & Senapati, T. (2024). A novel BWM-entropy-COPRAS group decision framework with spherical fuzzy information for digital supply chain partner selection. Complex & Intelligent Systems, 10(5), 6983–7008. https://doi.org/10.1007/s40747-024-01500-5.
Goldani, N., & Ishizaka, A. (2025). A hybrid fuzzy multi-criteria group decision-making method and its application to healthcare waste treatment technology selection. Annals of Operations Research, 353(1). https://doi.org/10.1007/s10479-024-06036-y.
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). https://doi.org/10.1007/s00521-022-07929-4.
Kaya, S. K., Pamucar, D., & Aycin, E. (2022). A New Hybrid Fuzzy Multi-Criteria Decision Methodology for Prioritizing the Antivirus Mask over COVID-19 Pandemic. Informatica (Netherlands), 33(3). https://doi.org/10.15388/22-INFOR475.
Ortiz-Barrios, M., Cleland, I., Donnelly, M., Gul, M., Yucesan, M., Jiménez-Delgado, G. I., Nugent, C., & Madrid-Sierra, S. (2024). Integrated Approach Using Intuitionistic Fuzzy Multicriteria Decision-Making to  Support Classifier Selection for Technology Adoption in Patients with Parkinson Disease: Algorithm Development and Validation. JMIR Rehabilitation and Assistive Technologies, 11, e57940. https://doi.org/10.2196/57940.
Ortíz-Barrios, M., Jaramillo-Rueda, N., Gul, M., Yucesan, M., Jiménez-Delgado, G., & Alfaro-Saíz, J. J. (2023). A Fuzzy Hybrid MCDM Approach for Assessing the Emergency Department Performance during the COVID-19 Outbreak. International Journal of Environmental Research and Public Health, 20(5). https://doi.org/10.3390/ijerph20054591.
Pazhouhandeh, A., & Samouei, P. (2024). Predictive and simultaneous weighting of criteria and alternatives (PSWCA) in multi-criteria decision making based on past data. Soft Computing, 28(5). https://doi.org/10.1007/s00500-023-09595-7.
Puška, A., Štilić, A., Pamucar, D., Simic, V., & Petrović, N. (2024). Optimal selection of healthcare waste treatment devices using fuzzy-rough approach. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-024-32630-5.
Raveena, R., & Umamaheswari, S. (2025). Integrated MCDM framework for sustainable pharmacy supplier selection using pioneering criteria with fuzzy TOPSIS SVR and GRA. Scientific Reports, 15(1), 19144. https://doi.org/10.1038/s41598-025-02975-z.
Saleh, N., Gaber, M. N., Eldosoky, M. A., & Soliman, A. M. (2023). Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-38902-3.
Satria, M. N. D., Susanto, E. R., Setiawansyah, Maryana, S., & Palupiningsih, P. (2025). modification of grey relational analysis for dynamic criteria weighting in decision-making systems. IIUM Engineering Journal, 26(2). https://doi.org/10.31436/iiumej.v26i2.3494.
Shbool, M. A., Arabeyyat, O. S., Al-Bazi, A., & AlAlaween, W. H. (2021). An integrated multi-criteria decision-making framework for a medical device selection in the healthcare industry. Cogent Engineering, 8(1). https://doi.org/10.1080/23311916.2021.1968741.
Singh, R., Pathak, V. K., Kumar, R., Dikshit, M., Aherwar, A., Singh, V., & Singh, T. (2024). A historical review and analysis on MOORA and its fuzzy extensions for different applications. Heliyon, 10(3). https://doi.org/10.1016/j.heliyon.2024.e25453.
Sotoudeh-Anvari, A. (2022). The applications of MCDM methods in COVID-19 pandemic: A state of the art review. In Applied Soft Computing (Vol. 126). https://doi.org/10.1016/j.asoc.2022.109238.
Taherdoost, H., & Madanchian, M. (2023). Multi-Criteria Decision Making (MCDM) Methods and Concepts. Encyclopedia, 3(1). https://doi.org/10.3390/encyclopedia3010006.
Torkayesh, A. E., Deveci, M., Karagoz, S., & Antucheviciene, J. (2023). A state-of-the-art survey of evaluation based on distance from average solution (EDAS): Developments and applications. Expert Systems with Applications, 221. https://doi.org/10.1016/j.eswa.2023.119724.
Yadav, N., Ahmad, S., & Khan, N. (2018). Analyzing Healthcare Device Security through Fuzzy Rule-based Multi-criteria Model. EAI Endorsed Transactions on Context-Aware Systems and Applications. https://doi.org/10.4108/eai.16-5-2022.173978.