Pereira Libório Matheus, Ekel Petr Iakovlevitch, Laudares Sandro, Martins Carlos Augusto Paiva da Silva
Pontifical Catholic University of Minas Gerais, 500 Dom José Gaspar Street, Belo Horizonte, MG 30535-901, Brazil.
MethodsX. 2024 Jan 17;12:102575. doi: 10.1016/j.mex.2024.102575. eCollection 2024 Jun.
The Ordered Weighted Averaging (OWA) operator is a multicriteria method that has conquered space among researchers in the composite indicators field. Typically, OWA operator weights are defined by the decision maker. This type of weighting is highly criticized, as decision-makers are susceptible to errors and bias in judgment. Some methods have been used to define OWA operator weights objectively. However, none of them is concerned about the quality of the composite indicator. This paper introduces a method that defines the weights of the OWA operator based on two quality parameters of the composite indicator: the ability to capture the concept of the multidimensional phenomenon and the informational loss. The method can be implemented in Microsoft Excel Solver and has a high degree of flexibility and applicability in problems of a multidimensional nature and a high degree of appropriation by researchers and practitioners in the area.•Defines weights that maximize the ability of the composite indicator to capture the concept of the multidimensional phenomenon.•Considers restrictions to limit the informational loss of the composite indicator or emphasize positive or negative aspects of the multidimensional phenomenon.•Offers flexibility in setting the objective and constraints of the optimization algorithm.
有序加权平均（OWA）算子是一种多准则方法，在综合指标领域的研究人员中占据了一席之地。通常，OWA算子的权重由决策者定义。这种加权方式受到了严厉批评，因为决策者在判断时容易出现错误和偏差。一些方法已被用于客观地定义OWA算子的权重。然而，它们都没有考虑综合指标的质量。本文介绍了一种基于综合指标的两个质量参数来定义OWA算子权重的方法：捕捉多维现象概念的能力和信息损失。该方法可以在Microsoft Excel Solver中实现，在多维性质的问题中具有高度的灵活性和适用性，并且受到该领域研究人员和从业者的高度认可。
定义权重，使综合指标捕捉多维现象概念的能力最大化。
考虑限制条件，以限制综合指标的信息损失或强调多维现象的积极或消极方面。
在设置优化算法的目标和约束方面提供灵活性。
