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Efficient pairwise preference elicitation allowing for indifference

机译:高效的成对偏好诱导,可以保持冷漠

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Many methods in Multi-Criteria Decision Analysis for choice problems rely on eliciting pairwise preference information in their attempt to efficiently identify the most preferred solution out of a larger set of solutions. That is, they repeatedly ask the decision maker which of two solutions is preferred, and then use this information to reduce the number of possibly preferred solutions until only one remains. However, if the solutions have a very similar value to the decision maker, he/she may not be able to accurately decide which solution is preferred. This paper makes two main contributions. First, it extends Robust Ordinal Regression to allow a user to declare indifference in case the values of the two solutions do not differ by more than some.personal threshold. Second, we propose and compare several heuristics to pick pairs of solutions to be shown to the decision maker in order to minimize the number of interactions necessary. (C) 2017 Elsevier Ltd. All rights reserved.
机译:针对选择问题的多标准决策分析中的许多方法都依赖于获取成对偏好信息,以试图从一大套解决方案中有效地识别出最优选的解决方案。也就是说,他们反复询问决策者哪种方案是首选的,然后使用此信息减少可能的方案的数量,直到只剩下一种。但是,如果解决方案的价值与决策者非常相似,则他/她可能无法准确地确定首选哪种解决方案。本文有两个主要贡献。首先,它扩展了稳健的序数回归,以允许用户声明无差异,以防两种解决方案的值相差不超过个人阈值。其次,我们建议并比较几种启发式方法,以选择要显示给决策者的解决方案对,以最大程度地减少必要的交互次数。 (C)2017 Elsevier Ltd.保留所有权利。

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