{"title":"Combination weighting method using Z-numbers for multi-criteria decision-making","authors":"Huan-Jyh Shyur","doi":"10.1016/j.asoc.2025.112992","DOIUrl":null,"url":null,"abstract":"<div><div>This study introduces a hybrid approach to determining criteria weights in Multi-Criteria Decision Making (MCDM), combining subjective weight methods with objective weighting techniques based on Z-number theory. The methodology is applied in a practical context involving the establishment of a bank's call center data analysis platform. Leveraging the inherent uncertainty and reliability considerations in decision-making processes, the hybrid method offers a robust framework for decision support. Through empirical validation and case study analysis, the effectiveness of the proposed approach is demonstrated, highlighting its ability to balance theoretical robustness with practical applicability. The study underscores the importance of ongoing research in MCDM, particularly in developing innovative methods to address the complexities of decision-making environments. Insights from this research provide valuable guidance for practitioners and researchers seeking to enhance MCDM processes across diverse domains.</div></div>","PeriodicalId":50737,"journal":{"name":"Applied Soft Computing","volume":"174 ","pages":"Article 112992"},"PeriodicalIF":7.2000,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Soft Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1568494625003035","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This study introduces a hybrid approach to determining criteria weights in Multi-Criteria Decision Making (MCDM), combining subjective weight methods with objective weighting techniques based on Z-number theory. The methodology is applied in a practical context involving the establishment of a bank's call center data analysis platform. Leveraging the inherent uncertainty and reliability considerations in decision-making processes, the hybrid method offers a robust framework for decision support. Through empirical validation and case study analysis, the effectiveness of the proposed approach is demonstrated, highlighting its ability to balance theoretical robustness with practical applicability. The study underscores the importance of ongoing research in MCDM, particularly in developing innovative methods to address the complexities of decision-making environments. Insights from this research provide valuable guidance for practitioners and researchers seeking to enhance MCDM processes across diverse domains.
期刊介绍:
Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities.
Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.