Abstract: In practical fuzzy decision-making environments,decision-makers may face the challenge of using multiple fuzzy sets simultaneously to describe complex decision information.To address this issue,a novel hybrid hesitant fuzzy set that integrated interval-valued hesitant fuzzy sets,triangular hesitant fuzzy sets and traditional hesitant fuzzy sets was proposed aiming to provide a more flexible and precise decision-making information expression tool.By constructing a hybrid hesitant fuzzy distance measure based on the Canberra distance,the normalization process of the Criteria Importance through Intercriteria Correlation(CRITIC)method and the global preference scoring process of the Organisation,Rangement et Synthèse de Données Relationnelles(ORESTE)method were improved.Additionally,a CRITIC-ORESTE multi-criteria group decision-making method suitable for the hybrid hesitant fuzzy environment was proposed,which was validated through a practical case of selecting green supply chain partners.The results showed that the proposed method not only enhanced the accuracy of decision-making but also increased the flexibility of the decision process.

Key words: hybrid hesitant fuzzy sets, rganisation,rangement et synthèse de données relationnelles, criteria importance through intercriteria correlation, multi-criteria group decision-making, distance measurment

摘要： 在实际的模糊决策环境中,决策者可能面临需要同时运用多种模糊集来描述复杂决策信息的挑战。针对此问题,提出一种新的混合犹豫模糊集,该集合融合了区间值犹豫模糊集、三角犹豫模糊集以及传统犹豫模糊集,旨在提供一种更为灵活且精确的决策信息表达工具。通过构建基于堪培拉距离的混合犹豫模糊距离测度公式,进一步改进了CRITIC方法的标准化过程和ORESTE方法的全局偏好评分过程。此外,还提出了一个适用于混合犹豫模糊环境的CRITIC-ORESTE多准则群决策方法,并通过绿色供应商合作伙伴选择的实际案例进行了验证。结果显示,所提方法不仅提高了决策的准确性,还增强了决策过程的灵活性。

关键词: 混合犹豫模糊集, ORESTE, CRITIC, 多准则群决策, 距离测度