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

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 LI...

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Bibliographic Details
Published in:Applied intelligence (Dordrecht, Netherlands) Vol. 55; no. 7; p. 600
Main Authors: Wan, Shu-Ping, Gao, Yu, Dong, Jiu-Ying
Format: Journal Article
Language:English
Published: New York Springer US 01.05.2025
Springer Nature B.V
Subjects:
Alternatives
Artificial Intelligence
Computer Science
Conditional probability
Decision making
Linear programming
Machines
Manufacturing
Mechanical Engineering
Optimization models
Processes
Teachers
China
LINMAP (Linear Programming Technique for Multidimensional Analysis of Preference)
Three-way decisions
Multi-attribute group decision-making
College teacher introduction
ISSN:0924-669X, 1573-7497
Online Access:Get full text
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Summary: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.
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ISSN:0924-669X
1573-7497
DOI:10.1007/s10489-025-06369-6