Many advances in artificial intelligence and machine learning are based on decision making, especially in uncertain settings. Due to its possible applications, decision making is currently a broad field of study in many areas like Computation, Economics and Business Management. The first techniques appeared in scenarios where information was modeled by real numbers. In all cases, one of the key steps in such processes was the summarization of the available information into a few values that helped the decision maker to complete this task. In this paper, we introduce a novel multi-criteria decision making methodology in the fuzzy context in which weights and experts’ opinions (maybe translated by linguistic labels) are stated as triangular fuzzy numbers. To do that, we take advantage of a recently presented fuzzy binary relation whose properties are according to human intuition and we carry out an study of the main properties that an aggregation function (a mapping to sum up information) must satisfy in the fuzzy framework. The presented procedure makes a final decision based on parabolic fuzzy numbers (not triangular). And this will be shown in an illustrative example.

人工智能和机器学习的许多进步都基于决策，尤其是在不确定的环境中。由于其可能的应用，决策是当前在计算，经济学和业务管理等许多领域中广泛的研究领域。最早的技术出现在通过实数对信息建模的场景中。在所有情况下，此类过程中的关键步骤之一就是将可用信息汇总为几个值，以帮助决策者完成此任务。在本文中，我们介绍了一种在模糊上下文中将权重和专家意见（可能由语言标签翻译）表示为三角模糊数的新颖的多准则决策方法。要做到这一点，我们利用了最近提出的模糊二元关系，该模糊二元关系的性质是根据​​人类的直觉而定的，并且我们对聚合函数（用于汇总信息的映射）必须满足的主要性质进行了研究。提出的过程基于抛物线模糊数（不是三角形）做出最终决定。并且这将在说明性示例中示出。