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Preference disaggregation method for value-based multi-decision sorting problems with a real-world application in nanotechnology
Knowledge-Based Systems ( IF 8.8 ) Pub Date : 2021-02-18 , DOI: 10.1016/j.knosys.2021.106879
Miłosz Kadziński , Krzysztof Martyn , Marco Cinelli , Roman Słowiński , Salvatore Corrente , Salvatore Greco

We consider a problem of multi-decision sorting subject to multiple criteria. In the newly formulated decision problem, besides performances on multiple criteria, alternatives get evaluations on multiple interrelated decision attributes involving preference-ordered classes. We propose a dedicated method for dealing with such a problem, incorporating a threshold-based value-driven sorting procedure. The Decision Maker (DM) is expected to holistically evaluate a subset of reference alternatives by indicating the quality or risk level on a pre-defined scale of each decision attribute. Based on these evaluations, we construct a set of interrelated preference models, one for each decision attribute, compatible with intra- and inter-decision constraints imposed by such indirect preference information. We also formulate a new way of dealing with potentially non-monotonic criteria by discovering local monotonicity changes in different performance scale regions. The marginal value functions for criteria with unknown monotonicity are represented as a sum of two value functions assuming opposing preference directions, one non-decreasing and the other non-increasing. This permits to obtain an aggregated marginal value function with an arbitrary non-monotonic shape. The practical usefulness of the approach is demonstrated on a case study concerning risk management related to handling (i.e., production, use, manipulation, and processing) nanomaterials in different conditions. We analyze the expert judgments and discuss the inferred preference models, which can be applied to support health and safety managers in reducing the possible risk associated with the respective exposure scenario.



中文翻译:

基于价值的多决策排序问题的偏好分解方法及其在纳米技术中的实际应用

我们考虑一个受多个标准约束的多决策排序问题。在新制定的决策问题中,除了可以在多个标准上执行之外,替代方案还可以对涉及偏好排序类的多个相互关联的决策属性进行评估。我们提出了一种专门的方法来处理此类问题,并结合了基于阈值的价值驱动的排序程序。决策者(DM)希望通过在每个决策属性的预定义尺度上指示质量或风险级别来整体评估参考备选方案的子集。基于这些评估,我们构造了一组相互关联的偏好模型,每个决策属性对应一个模型,这些模型与此类间接偏好信息所施加的内部和内部决策约束兼容。我们还通过发现不同绩效规模区域中的局部单调性变化,制定了一种处理潜在非单调性准则的新方法。具有未知单调性的准则的边际值函数表示为两个值函数的总和,这些函数假设相反的偏好方向,一个不变,另一个不变。这允许获得具有任意非单调形状的合计边际值函数。在涉及与在不同条件下处理(即生产,使用,操纵和加工)纳米材料有关的风险管理的案例研究中,证明了该方法的实用性。我们分析专家的判断并讨论推断的偏好模型,

更新日期:2021-02-28
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