JOURNAL ARTICLE
An Integrated Interval Type-2 Fuzzy PROMETHEE-II Decision Model for the Selection of Medical Waste Treatment Techniques.
Published In: International Journal of Information Technology & Decision Making, 2025, v. 24, n. 4. P. 1035 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Tang, Jing; Liu, Xinwang; Wang, Weizhong 3 of 3
Abstract
The selection of medical waste treatment techniques has become a serious health and safety issue since the amount and variety of medical waste are rapidly increasing during the Corona Virus Disease 2019 (COVID-19) pandemic in the whole world. This paper aims to propose an integrated interval type-2 fuzzy Preference Ranking Organization Method for Enrichment Evaluations-II (PROMETHEE-II) decision model for medical waste treatment techniques selection problem considering interactive relationships among criteria under a high uncertain environment. First, interval type-2 fuzzy sets (IT2FSs) are introduced to express imprecision information within the context of high uncertainty. Second, a type-2 Prioritized Aggregation (PA) operator is constructed to aggregate the evaluation information considering the priority of experts. Third, the Decision Making Trial and Evaluation Laboratory (DEMATEL) method is combined with the IT2FS to calculate the weights of criteria considering the interaction relationships among them. Then, an extended interval type-2 fuzzy PROMETHEE-II method is proposed to rank each alternative, in which a distance measure-based preference function is adopted. After that, a case study of medical waste treatment selection in Jiangsu province is used to illustrate the effectiveness of the proposed approach. The results demonstrate that incineration is the most appropriate approach in handling medical waste. Finally, sensitivity analysis and comparative analysis are implemented to further test the advantages of the proposed approach. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Information Technology & Decision Making. 2025/05, Vol. 24, Issue 4, p1035
- Document Type:Article
- Subject Area:Science
- Publication Date:2025
- ISSN:0219-6220
- DOI:10.1142/S0219622023500554
- Accession Number:185626504
- Copyright Statement:Copyright of International Journal of Information Technology & Decision Making is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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