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Using assignment examples to infer weights for ELECTRE TRI method: Some experimental results

机译:使用赋值示例推断ELECTRE TRI方法的权重:一些实验结果

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摘要

Given a finite set of alternatives A, the sorting (or assignment) problem consists in the assignment of each alternative to one of the pre-defined categories. In this paper, we are interested in multiple criteria sorting problems and, more precisely, in the existing method ELECTRE TRI. This method requires the elicitation of preferential parameters (weights, thresholds, category limits,...) in order to construct a preference model which the decision maker (DM) accepts as a working hypothesis in the decision aid study. A direct elicitation of these parameters requiring a high cognitive effort from the DM (V. Mosseau, R. Slowinski, Journal of Global Optimization 12 (2) (1998) 174), proposed an interactive aggregation-disaggregation approach that infers ELECTRE TRI parameters indirectly from holistic information, i.e., assignment examples. In this approach, the determination of ELECTRE TRI parameters that best restore the assignment examples is formulated through a nonlinear optimization program.
机译:给定一组有限的备选方案A,排序(或分配)问题在于将每个备选方案分配给一个预定义的类别之一。在本文中,我们对多个标准排序问题感兴趣,更确切地说,对现有方法ELECTRE TRI感兴趣。此方法需要引发优先参数(权重,阈值,类别限制等),以构建偏好模型,决策者(DM)将其接受为决策辅助研究中的有效假设。对这些参数的直接启发需要DM的高度认知努力(V.Mosseau,R.Slowinski,Journal of Global Optimization 12(2)(1998)174),提出了一种交互式聚集-分解方法,可间接推断ELECTRE TRI参数来自整体信息,即作业示例。通过这种方法,可以通过非线性优化程序确定最能恢复分配示例的ELECTRE TRI参数。

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