研究决策方案有不完全类别偏好信息的多属性决策方法。基于TOPSIS理想点的分析框架,表征同类别方案之间的相对贴近度和不同类别方案之间的平均贴近度;建立了考虑方案有不完全类别偏好的属性权重估测模型,设计了不完全类别偏好的案例学习和决策方法。实证比较表明了方法的应用步骤和有效性。 Research on multi-attribute decision-making methods with incomplete category preference information. Based on the analysis framework of TOPSIS ideal points, the paper presents the relative closeness between programs of the same category and the average closeness between different categories of programs. An attribute weight estimation model considering the partial preference of programs is established, and the incomplete categories Preferred case study and decision making methods. Empirical comparison shows the method of application of the method and effectiveness.