多属性相对变权决策模型及方法

为克服多因素变权决策方法以及多属性决策Choquet积分模型没有科学反映多属性决策过程中决策者点依赖偏好关联行为的技术缺陷，在借鉴摆幅置权方法和网络分析法技术要点的基础上，运用数据包络分析的相对评价思维，提出一种全新的评价与决策方法即多属性相对变权决策方法。相对于多因素变权决策方法，新方法可以直接反映决策者的点依赖偏好结构，从而可以克服前者在反映点依赖偏好关联行为上所存在的源于决策分析者的武断随意性；相对于多属性决策Choquet积分模型，新方法可以反映决策者的点依赖偏好关联行为，并且在多数实际决策场合可以较有效地规避Choquet积分模型在决策参数判断上的指数复杂性难题。案例应用验证表明：新方法可以给出与决策者关于偏好依赖关联定性看法及客观事实非常相符的选择结论，可以更好地反映决策者的具体偏好。

Model and Method of Multiple Attribute Decision Making with Relative Variable Weights

Both the multiple factor decision-making method based on variable weights (MFDMM-VW) and the Choquet integral model (CIM) for multiple attribute decision-making (MADM) cannot reflect reasonably the decision-maker's point-dependence preference in MADM. To overcome the mentioned shortcoming, a new MADM approach to evaluation and decision making, i.e., the MADM model with relative variable weights (MADMM-RVW), and its corresponding method are presented based on the swing-weighting, the analytic network process, and the relative evaluation thought embodied in data envelopment analysis. Compared with the MFDMM-VW, the MADMM-RVW is able to reflect directly the decision-maker's point-dependence preference structure, and thus overcome the arbitrariness of the MFDMM-VW in reflecting the decision-maker's point-dependence preference, resulted from decision analysts when the MFDMM-VW is applied. Compared with the CIM, the MADMM-RVW can not only reflect the decision-maker's point-dependence preference but also avoid more efficiently the CIM's large-scale estimation problem of decision parameters in many MADM cases. Applied in a case study, the MADMM-RVW is showed to give decision conclusions well consistent with objective existence and the decision-maker's qualitative opinions on preference dependence, and thus be capable of better reflecting the decision-maker's specific preference behaviors.