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Dynamic multi-attribute decision making model with the area closeness Degree

机译:具有区域近度度的动态多属性决策模型

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The aim of this paper is to explore dynamic multi-attribute decision making (DMADM) problems in which the decision making information of alternatives is collected at different stages. Firstly, the area closeness degree is applied in normalizing the raw data. Secondly, the weights of different stages are determined by according to the principle of new information priority. The technique for preference by similarity to ideal solution (TOPSIS) is improved to aggregate the information from different stages. Finally, the example is illustrated to demonstrate the practicality and effectiveness of the proposed methods.
机译:本文的目的是探索动态多属性决策(DMADM)问题,其中在不同阶段收集替代品的决策信息。首先,将面积的接近度归一化原始数据。其次,通过根据新信息优先级的原理来确定不同阶段的权重。通过相似性与理想解决方案(TOPSIS)的相似性的技术得到改善,以聚合来自不同阶段的信息。最后,说明了该示例以证明所提出的方法的实用性和有效性。

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