Dynamic Multi-Attribute Decision Making Model with the Area Closeness Degree

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 321-324)
• Pages: 2557-2560
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.321-324.2557
• Online since: June 2013
• Authors: Xi Juan Lou
• Keywords: Area Closeness Degree, Dynamic Measurement, Dynamic Multi-Attribute Decision Making, Influence of Normalize Methods, TOPSIS

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