Dynamic multi-attribute decision-making model and application with interval number based on improved vector similarity

被引：0

作者：

Qian W.-Y. ^{[1
]}

Dong Y.-B. ^{[1
]}

机构：

[1] School of Business, Jiangnan University, Wuxi

来源：

Kongzhi yu Juece/Control and Decision | 2019年 / 34卷 / 01期

关键词：

Interval number relative similarity relation; Maximum entropy principle; Multiple attribute decision-making; Vector similarity;

D O I：

10.13195/j.kzyjc.2018.0110

中图分类号：

学科分类号：

摘要：

For the uncertain dynamic decision-making problem that the decision information is interval number, under the condition that the attribute weights and time weights are unknown, a dynamic multiple attribute decision-making model considering both decision information and decision preference based on improved vector similarity is proposed. Based on the relative similarity relations of the interval decision information and the importance of attribute, the relative similarity degree minimum programming model is constructed to determine the index weights. Taking the time value of decision information and the decision maker's preference into account, the maximum entropy model is established to determine the time weights. Combining the shortcoming of vector similarity calculation, a measure method of vector similarity based on vector projection idea is given, so that the uncertain dynamic decision-making model is constrated. Finally, an example is given to illustrate the rationality and effectiveness of the proposed model. © 2019, Editorial Office of Control and Decision. All right reserved.

引用

页码：25 / 30

页数：5

共 21 条

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