Identifying conflict patterns to reach a consensus - A novel group decision approach

NCU Institutional Repository > 管理學院 > 資訊管理學系 > 期刊論文 > Item 987654321/106748

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://ir.lib.ncu.edu.tw/handle/987654321/106748

题名:	Identifying conflict patterns to reach a consensus - A novel group decision approach
作者:	陳彥良;Cheng, Li-Chen;Chen, Yen-Liang;Chiang, Yu-Chia
贡献者:	管理學院資訊管理學系
关键词:	Algorithms;Computational efficiency;Conflict;Conflict patterns;Data mining;Decision making units;Decision-making;Group decision-making;Group dynamics;Maximum consensus sequence;Operational research;Order disorder;Ranking;Studies
日期:	2016-10-16
上传时间:	2026-04-23 13:39:21 (UTC+8)
出版者:	Elsevier;Amsterdam: Elsevier B.V
摘要:	摘要： •In real organizations, diversity of experts always solve complex and emergent problems.•The conflict-elimination process is minimizing the degree of conflict arising from different backgrounds experts’ opinion.•The conflict patterns can reveal the ranking of what alternatives are the most controversial among decision makers.•We proposed the Mining Conflict Pattern (MCP) algorithm to find conflict patterns from users’ partial ranking data. In recent years, the group ranking problem has become an important subject of study. In most group ranking problems, the focus is on identifying consensuses. No previous research has involved identifying conflicting opinions, called conflict patterns in this paper, among decision-makers. We define conflict patterns as orderings of alternatives that have roughly the same numbers of advantages and disadvantages. Conflict patterns can reveal the ranking of which alternatives are the most controversial among decision-makers and who the supporters and opponents are. Using conflict pattern data, decision-makers can communicate with people with differing opinions and attempt to resolve the differences. In this study, an algorithm, Mining Conflict Patterns, was developed to identify conflict patterns from users’ partial ranking data. Extensive experiments were conducted using synthetic and real data sets. The results indicate that the proposed method is computationally efficient and can effectively identify conflict patterns among all users. 出版者： Amsterdam: Elsevier B.V 出版日期： 2016-10-16 出處： European journal of operational research, 2016-10, Vol.254 (2), p.622-631 版權： 2016 Elsevier B.V. 版權： Copyright Elsevier Sequoia S.A. Oct 16, 2016 識別號： ISSN: 0377-2217 識別號： EISSN: 1872-6860 識別號： DOI: 10.1016/j.ejor.2016.04.004 識別號： CODEN: EJORDT
显示于类别:	[資訊管理學系] 期刊論文

文件中的档案:

档案	描述	大小	格式	浏览次数
index.html		0Kb	HTML	29	检视/开启

在NCUIR中所有的数据项都受到原著作权保护.

社群 sharing

数据加载中.....