Normalization and aggregation are two most important issues in multi-criteria analysis. Although various multi-criteria decision-making (MCDM) methods have been developed over the past several decades, few of them integrate multiple normalization techniques and mixed aggregation approaches at the same time to reduce the deviations of evaluation values and enhance the reliability of the final decision result. This study is dedicated to introducing a new MCDM method called Mixed Aggregation by COmprehensive Normalization Technique (MACONT) to tackle complicate MCDM problems. This method introduces a comprehensive normalization technique based on criterion types, and then uses two mixed aggregation operators to aggregate the distance values between each alternative and the reference alternative on different criteria from the perspectives of compensation and non-compensation. An illustrative example is given to show the applicability of the proposed method, and the advantages of the proposed method are highlighted through sensitivity analyses and comparative analyses.

中文翻译：

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MACONT：通过综合归一化技术进行多标准分析的混合聚合

归一化和聚合是多标准分析中两个最重要的问题。尽管在过去的几十年里已经发展了各种多标准决策（MCDM）方法，但很少有人同时集成多种归一化技术和混合聚合方法来减少评估值的偏差并提高最终结果的可靠性。决策结果。本研究致力于引入一种新的 MCDM 方法，称为综合归一化技术 (MACONT) 的混合聚合，以解决复杂的 MCDM 问题。该方法引入了一种基于标准类型的综合归一化技术，然后使用两个混合聚合算子，从补偿和非补偿的角度，根据不同的标准，聚合每个备选方案与参考备选方案之间的距离值。举例说明了所提出方法的适用性，并通过敏感性分析和比较分析突出了所提出方法的优点。