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Pazhouhandeh, Arash, Samouei, Parvaneh. (1404). Fuzzy Multi-Criteria Decision-Making Method F-PSWCA: A Case Study on the Selection and Ranking of Criteria and New Technologies in Dialysis. , (), -. doi: 10.22059/aie.2026.405928.1959
Arash Pazhouhandeh; Parvaneh Samouei. "Fuzzy Multi-Criteria Decision-Making Method F-PSWCA: A Case Study on the Selection and Ranking of Criteria and New Technologies in Dialysis". , , , 1404, -. doi: 10.22059/aie.2026.405928.1959
Pazhouhandeh, Arash, Samouei, Parvaneh. (1404). 'Fuzzy Multi-Criteria Decision-Making Method F-PSWCA: A Case Study on the Selection and Ranking of Criteria and New Technologies in Dialysis', , (), pp. -. doi: 10.22059/aie.2026.405928.1959
Pazhouhandeh, Arash, Samouei, Parvaneh. Fuzzy Multi-Criteria Decision-Making Method F-PSWCA: A Case Study on the Selection and Ranking of Criteria and New Technologies in Dialysis. , 1404; (): -. doi: 10.22059/aie.2026.405928.1959

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

Advances in Industrial Engineering
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 05 بهمن 1404
شناسه دیجیتال (DOI): 10.22059/aie.2026.405928.1959
نویسندگان
Arash Pazhouhandeh1؛ Parvaneh Samouei* 2
1PhD candidate., Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
2shahid ahmadi roushan Blvd.
چکیده
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.
کلیدواژه‌ها
Fuzzy regression؛ Fuzzy decision-making؛ Innovation ranking؛ Dialysis
آمار
تعداد مشاهده مقاله: 92





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