A novel three-way heterogeneous multi-attribute group decision method based on LINMAP for college teacher introduction

IF 3.4 2区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Shu-Ping Wan, Yu Gao, Jiu-Ying Dong
{"title":"A novel three-way heterogeneous multi-attribute group decision method based on LINMAP for college teacher introduction","authors":"Shu-Ping Wan,&nbsp;Yu Gao,&nbsp;Jiu-Ying Dong","doi":"10.1007/s10489-025-06369-6","DOIUrl":null,"url":null,"abstract":"<div><p>With dramatic development of Chinese social economics and higher education, college teacher introduction has become an urgent and important problem, which is a type of heterogeneous multi-attribute group decision-making (HMAGDM). This article erects a novel three-way decision (TWD) model based on LINMAP (Linear Programming Technique for Multidimensional Analysis of Preference) to handle HMAGDM and applies to college teacher introduction. Firstly, combining evaluation matrices with alternatives’ preferences offered by decision makers (DMs), we define the individual consistency and inconsistency indexes, group consistency and inconsistency indexes. In terms of the individual consistency and inconsistency indexes, the weights of DMs are determined through establishing a bi-objective mathematical optimization model. As per the group consistency and inconsistency indexes, we build a bi-objective optimization model to derive the attribute weights and the fuzzy ideal solutions (FISs) which are employed to calculate the relative profit functions. Using the DMs’ weights, we could obtain the collective overall profit functions of alternatives and the thresholds. The conditional probability of each alternative is acquired according to the relative closeness coefficient. The classification rules and decision results are further induced based on maximum-profit decision principle. An example of college teacher introduction is illustrated to verify the efficacy of the erected method.</p></div>","PeriodicalId":8041,"journal":{"name":"Applied Intelligence","volume":"55 7","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Intelligence","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s10489-025-06369-6","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

With dramatic development of Chinese social economics and higher education, college teacher introduction has become an urgent and important problem, which is a type of heterogeneous multi-attribute group decision-making (HMAGDM). This article erects a novel three-way decision (TWD) model based on LINMAP (Linear Programming Technique for Multidimensional Analysis of Preference) to handle HMAGDM and applies to college teacher introduction. Firstly, combining evaluation matrices with alternatives’ preferences offered by decision makers (DMs), we define the individual consistency and inconsistency indexes, group consistency and inconsistency indexes. In terms of the individual consistency and inconsistency indexes, the weights of DMs are determined through establishing a bi-objective mathematical optimization model. As per the group consistency and inconsistency indexes, we build a bi-objective optimization model to derive the attribute weights and the fuzzy ideal solutions (FISs) which are employed to calculate the relative profit functions. Using the DMs’ weights, we could obtain the collective overall profit functions of alternatives and the thresholds. The conditional probability of each alternative is acquired according to the relative closeness coefficient. The classification rules and decision results are further induced based on maximum-profit decision principle. An example of college teacher introduction is illustrated to verify the efficacy of the erected method.

求助全文
约1分钟内获得全文 求助全文
来源期刊
Applied Intelligence
Applied Intelligence 工程技术-计算机:人工智能
CiteScore
6.60
自引率
20.80%
发文量
1361
审稿时长
5.9 months
期刊介绍: With a focus on research in artificial intelligence and neural networks, this journal addresses issues involving solutions of real-life manufacturing, defense, management, government and industrial problems which are too complex to be solved through conventional approaches and require the simulation of intelligent thought processes, heuristics, applications of knowledge, and distributed and parallel processing. The integration of these multiple approaches in solving complex problems is of particular importance. The journal presents new and original research and technological developments, addressing real and complex issues applicable to difficult problems. It provides a medium for exchanging scientific research and technological achievements accomplished by the international community.
×
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