论文标题
通过随机反向分析鉴定多准则分类问题中的Choquet能力
Identification of Choquet capacity in multicriteria sorting problems through stochastic inverse analysis
论文作者
论文摘要
在多准则决策辅助（MCDA）中，Choquet积分已被用作聚合操作员来应对交互决策标准的情况。尽管Choquet积分在排名问题上的应用一直受到大部分关注，但本文却着重于多标准排序问题（MCSP）。在Choquet积分环境中，出现的实际问题与称为Choquet能力的参数启发有关。我们通过应用随机可接受性多标准分析（SMAA）来解决MCSP的Choquet容量识别问题，并提出了SMAA-S-CHOQUET方法。所提出的方法还能够对决策矩阵和限制概要文件中可能存在的不确定数据建模，后者是与分类有问题相关的参数。我们还引入了两种新的描述性措施，以便对能力进行反向分析：场景可接受性指数和中心容量向量。
In multicriteria decision aiding (MCDA), the Choquet integral has been used as an aggregation operator to deal with the case of interacting decision criteria. While the application of the Choquet integral for ranking problems have been receiving most of the attention, this paper rather focuses on multicriteria sorting problems (MCSP). In the Choquet integral context, a practical problem that arises is related to the elicitation of parameters known as the Choquet capacities. We address the problem of Choquet capacity identification for MCSP by applying the Stochastic Acceptability Multicriteri Analysis (SMAA), proposing the SMAA-S-Choquet method. The proposed method is also able to model uncertain data that may be present in both decision matrix and limiting profiles, the latter a parameter associated with the sorting problematic. We also introduce two new descriptive measures in order to conduct reverse analysis regarding the capacities: the Scenario Acceptability Index and the Scenario Central Capacity vector.
