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
