Open Access

ARTICLE

Group Decision-Making Model of Renal Cancer Surgery Options Using Entropy Fuzzy Element Aczel-Alsina Weighted Aggregation Operators under the Environment of Fuzzy Multi-Sets

Jing Fu^1,2, Jun Ye³, Liping Xie^1,*

1 Department of Urology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, China
2 Department of Urology, Shaoxing Second Hospital, Shaoxing, 312000, China
3 School of Civil and Environmental Engineering, Ningbo University, Ningbo, 315211, China

* Corresponding Author:Liping Xie. Email:

(This article belongs to the Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)

Computer Modeling in Engineering & Sciences 2022, 130(3), 1751-1769. https://doi.org/10.32604/cmes.2022.018739

Received 14 August 2021; Accepted 28 September 2021; Issue published 30 December 2021

Abstract

Since existing selection methods of surgical treatment schemes of renal cancer patients mainly depend on physicians’ clinical experience and judgments, the surgical treatment options of renal cancer patients lack their scientifical and reasonable information expression and group decision-making model for renal cancer patients. Fuzzy multi-sets (FMSs) have a number of properties, which make them suitable for expressing the uncertain information of medical diagnoses and treatments in group decision-making (GDM) problems. To choose the most appropriate surgical treatment scheme for a patient with localized renal cell carcinoma (RCC) (T1 stage kidney tumor), this article needs to develop an effective GDM model based on the fuzzy multivalued evaluation information of the renal cancer patients. First, we propose a conversion method of transforming FMSs into entropy fuzzy sets (EFSs) based on the mean and Shannon entropy of a fuzzy sequence in FMS to reasonably simplify the information expression and operations of FMSs and define the score function of an entropy fuzzy element (EFE) for ranking EFEs. Second, we present the Aczel-Alsina t-norm and t-conorm operations of EFEs and the EFE Aczel-Alsina weighted arithmetic averaging (EFEAAWAA) and EFE Aczel-Alsina weighted geometric averaging (EFEAAWGA) operators. Third, we develop a multicriteria GDM model of renal cancer surgery options in the setting of FMSs. Finally, the proposed GDM model is applied to two clinical cases of renal cancer patients to choose the best surgical treatment scheme for a renal cancer patient in the setting of FMSs. The selected results of two clinical cases verify the efficiency and rationality of the proposed GDM model in the setting of FMSs.

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