Chen, LuXu, HaiyanPedrycz, Witold2024-05-192024-05-1920231566-25351872-6305https://doi.org10.1016/j.inffus.2023.101936https://hdl.handle.net/20.500.12713/5182Multi-criteria decision aiding/making (MCDA/M) approach and three-way decisions (3WD) are embedded into the framework of graph model for conflict resolution (GMCR). The objective of this study is to develop more reasonable preference ranking for decision makers (DMs) produced from the perspective of options. This implies further simplification of the underlying computing behind conflict resolution. More specifically, DMs' original option statements are evaluated by hesitant fuzzy sets (HFSs), then a three-way decisions approach is used to screen out the infeasible and rank the feasible option statements, and the feasible option statements' loss values of three-way decisions approach are determined based on the hesitant fuzzy (HF) evaluation values. In addition, based on the value of conditional probability of the feasible option statements, an improved option prioritization technique with objective weights is developed to efficiently rank the conflict states, so that it can efficiently reflect the intensity of the ranking. Then, considering the preference thresholds of DMs, new definitions of threshold stabilities are proposed. As demonstrated by the case study in the problem of a carbon emission conflict in supply chain under 3060 carbon peak and neutrality goal in China, the proposed novel three-way decisions graph model for conflict resolution (3WD-GMCR) framework can be widely applied to the realistic scenarios of decision-making. Compared with previous studies, the proposed approach can not only obtain the intensity ranking of conflict states, but also resolve complex large-scale conflicts effectively.eninfo:eu-repo/semantics/closedAccessGraph Model For Conflict ResolutionThree-Way DecisionsHesitant Fuzzy SetsOption PrioritizationCarbon Peak And NeutralityConflict analysis based on a novel three-way decisions graph model for conflict resolution method under hesitant fuzzy environmentArticle100WOS:0010518921000012-s2.0-85166644057N/A10.1016/j.inffus.2023.101936Q1