In three-way conflict analysis, preference-based conflict situations characterize agents' attitudes towards issues by formally modeling their preferences over pairs of issues. However, existing preference-based conflict models rely exclusively on three qualitative relations, namely, preference, converse, and indifference, to describe agents' attitudes towards issue pairs, which significantly limits their capacity in capturing the essence of conflict. To overcome this limitation, we introduce the concept of an intuitionistic fuzzy preference-based conflict situation that captures agents' attitudes towards issue pairs with finer granularity than that afforded by classical preference-based models. Afterwards, we develop intuitionistic fuzzy preference-based conflict measures within this framework, and construct three-way conflict analysis models for trisecting the set of agent pairs, the agent set, and the issue set. Additionally, relative loss functions built on the proposed conflict functions are employed to calculate thresholds for three-way conflict analysis. Finally, we present adjustment mechanism-based feasible strategies that simultaneously account for both adjustment magnitudes and conflict degrees, together with an algorithm for constructing such feasible strategies, and provide an illustrative example to demonstrate the validity and effectiveness of the proposed model.

翻译：在三支冲突分析中，基于偏好的冲突情境通过形式化建模智能体对议题对的偏好来描述其对议题的态度。然而，现有的基于偏好的冲突模型仅依赖偏好、逆偏好和无关性这三种定性关系来描述智能体对议题对的态度，这极大地限制了其捕捉冲突本质的能力。为克服这一局限，我们引入了直觉模糊偏好冲突情境的概念，该概念能以比经典偏好模型更精细的粒度刻画智能体对议题对的态度。随后，我们在此框架内发展了基于直觉模糊偏好的冲突度量，并构建了用于三分智能体对集合、智能体集合及议题集合的三支冲突分析模型。此外，基于所提出冲突函数构建的相对损失函数被用于计算三支冲突分析的阈值。最后，我们提出了基于调整机制的可行策略，该策略同时考虑调整幅度与冲突程度，并给出了构建此类可行策略的算法，同时通过示例验证了所提模型的有效性。