{"title":"MCDM technique using single-valued neutrosophic trigonometric weighted aggregation operators","authors":"Jun Ye, Shigui Du, Rui Yong","doi":"10.1080/23270012.2023.2264294","DOIUrl":null,"url":null,"abstract":"AbstractMotivated based on the trigonometric t-norm and t-conorm, the aims of this article are to present the trigonometric t-norm and t-conorm operational laws of SvNNs and then to propose the SvNN trigonometric weighted average and geometric aggregation operators for the modelling of a multiple criteria decision making (MCDM) technique in an inconsistent and indeterminate circumstance. To realize the aims, this paper first proposes the trigonometric t-norm and t-conorm operational laws of SvNNs, which contain the hybrid operations of the tangent and arctangent functions and the cotangent and inverse cotangent functions, and presents the SvNN trigonometric weighted average and geometric operators and their properties. Next, a MCDM technique is proposed in view of the presented two aggregation operators in the circumstance of SvNNs. In the end, an actual case of the choice issue of slope treatment schemes is provided to indicate the practicability and effectivity of the proposed MCDM technique.Keywords: Single-valued neutrosophic numbertrigonometric t-norm and t-conormtrigonometric weighted aggregation operatordecision making Data availabilityAll data are included in this study.Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":46290,"journal":{"name":"Journal of Management Analytics","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2023-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Management Analytics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23270012.2023.2264294","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
AbstractMotivated based on the trigonometric t-norm and t-conorm, the aims of this article are to present the trigonometric t-norm and t-conorm operational laws of SvNNs and then to propose the SvNN trigonometric weighted average and geometric aggregation operators for the modelling of a multiple criteria decision making (MCDM) technique in an inconsistent and indeterminate circumstance. To realize the aims, this paper first proposes the trigonometric t-norm and t-conorm operational laws of SvNNs, which contain the hybrid operations of the tangent and arctangent functions and the cotangent and inverse cotangent functions, and presents the SvNN trigonometric weighted average and geometric operators and their properties. Next, a MCDM technique is proposed in view of the presented two aggregation operators in the circumstance of SvNNs. In the end, an actual case of the choice issue of slope treatment schemes is provided to indicate the practicability and effectivity of the proposed MCDM technique.Keywords: Single-valued neutrosophic numbertrigonometric t-norm and t-conormtrigonometric weighted aggregation operatordecision making Data availabilityAll data are included in this study.Disclosure statementNo potential conflict of interest was reported by the author(s).
期刊介绍:
The Journal of Management Analytics (JMA) is dedicated to advancing the theory and application of data analytics in traditional business fields. It focuses on the intersection of data analytics with key disciplines such as accounting, finance, management, marketing, production/operations management, and supply chain management. JMA is particularly interested in research that explores the interface between data analytics and these business areas. The journal welcomes studies employing a range of research methods, including empirical research, big data analytics, data science, operations research, management science, decision science, and simulation modeling.