A Neutrosophic Number based Multi-Choice Best-Worst Multi-criteria Decision-Making Approach and its Applications

IF 0.6 Q4 ENGINEERING, INDUSTRIAL
Seema Bano, Gulzarul Hasan Md, Abdul Quddoos
{"title":"A Neutrosophic Number based Multi-Choice Best-Worst Multi-criteria Decision-Making Approach and its Applications","authors":"Seema Bano, Gulzarul Hasan Md, Abdul Quddoos","doi":"10.7232/iems.2023.22.3.224","DOIUrl":null,"url":null,"abstract":"The best-worst method (BWM) is an advantageous mathematical method for solving the problem of prioritization in real-life decision-making problems. It helps to provide consensus decision-making by minimizing inconsistency and weighing the factors. BWM takes pairwise comparisons as input parameters. To address such issues where multiple options are assigned by experts to pairwise comparisons, Multi-choice BWM was developed. This method has shown its application in handling various choices and choosing that choice for which inconsistency is minimized. In this work, we have incorporated neutrosophic fuzziness in multiple options of pairwise comparisons in the form of triangular neutrosophic numbers. Neutrosophic numbers provide us with membership, non-membership, and indeterminacy grades, which incorporate more information to handle uncertainty in real-life decision problems. We have proposed a mathematical framework to accommodate neutrosophic fuzzy theory, multiple choices, and best-worst method approaches for solving multi-criteria decision-making problems. To show the applicability of the proposed model and validate our study, the method has been experimented with three case studies. The results obtained are compared with previously proposed models. It shows that similar ranking orders are obtained using the proposed approach.","PeriodicalId":45245,"journal":{"name":"Industrial Engineering and Management Systems","volume":"48 1","pages":"0"},"PeriodicalIF":0.6000,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrial Engineering and Management Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7232/iems.2023.22.3.224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0

Abstract

The best-worst method (BWM) is an advantageous mathematical method for solving the problem of prioritization in real-life decision-making problems. It helps to provide consensus decision-making by minimizing inconsistency and weighing the factors. BWM takes pairwise comparisons as input parameters. To address such issues where multiple options are assigned by experts to pairwise comparisons, Multi-choice BWM was developed. This method has shown its application in handling various choices and choosing that choice for which inconsistency is minimized. In this work, we have incorporated neutrosophic fuzziness in multiple options of pairwise comparisons in the form of triangular neutrosophic numbers. Neutrosophic numbers provide us with membership, non-membership, and indeterminacy grades, which incorporate more information to handle uncertainty in real-life decision problems. We have proposed a mathematical framework to accommodate neutrosophic fuzzy theory, multiple choices, and best-worst method approaches for solving multi-criteria decision-making problems. To show the applicability of the proposed model and validate our study, the method has been experimented with three case studies. The results obtained are compared with previously proposed models. It shows that similar ranking orders are obtained using the proposed approach.
基于中性数的多选择最佳-最差多准则决策方法及其应用
最佳-最差方法(best-worst method, BWM)是解决现实决策问题中优先级问题的一种有利的数学方法。它通过最小化不一致和权衡因素来帮助提供一致的决策。BWM将两两比较作为输入参数。为了解决专家为两两比较分配多个选项的问题,开发了多选择BWM。该方法在处理各种选择和选择使不一致性最小化的选择方面已显示出其应用。在这项工作中,我们以三角形嗜中性数的形式将嗜中性模糊纳入两两比较的多种选择中。中性数字为我们提供了隶属、非隶属和不确定等级,它们包含了更多的信息来处理现实生活中的决策问题中的不确定性。我们提出了一个数学框架,以适应中性模糊理论,多重选择和最佳-最差方法方法来解决多准则决策问题。为了证明所提出的模型的适用性并验证我们的研究,该方法已通过三个案例研究进行了实验。所得结果与先前提出的模型进行了比较。结果表明,采用该方法可以得到相似的排序顺序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
2.20
自引率
28.60%
发文量
45
期刊介绍: Industrial Engineering and Management Systems (IEMS) covers all areas of industrial engineering and management sciences including but not limited to, applied statistics & data mining, business & information systems, computational intelligence & optimization, environment & energy, ergonomics & human factors, logistics & transportation, manufacturing systems, planning & scheduling, quality & reliability, supply chain management & inventory systems.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信