A Possibility Priority Degree Analyzing Process for Multiple Attributes Decision Making Problems
European Business & Management
Volume 4, Issue 2, March 2018, Pages: 44-54
Received: Dec. 6, 2017; Accepted: Jan. 4, 2018; Published: Jan. 19, 2018
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Authors
Mingming Hu, College of Mathematics and Information Science, Guangxi University, Nanning, China
Xinmiao Ye, College of Mathematics and Information Science, Guangxi University, Nanning, China
Jibin Lan, College of Mathematics and Information Science, Guangxi University, Nanning, China
Fang Liu, College of Mathematics and Information Science, Guangxi University, Nanning, China
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Abstract
A multiple attributes decision making model is wildly used and studied. The goal of multiple attributes decision making problems is to select a perfect alternative. The existed methods pay attention to rank the alternatives and suggest a best alternative to decision makers. However, there is risk hiding on the priority order. When accepting the order, decision makers undertake the risk at the same time. It is unknown for decision makers. To show the advantages and disadvantages for each alternative, and the risk of a selection, we propose a possibility priority degree analyzing model. With this model, decision makers can be aware of the possibility of priority degree, similar degree and the priority risk, and then make decision. It will effectively reduce the decision risk and improve the decision efficiency.
Keywords
MADM, Possibility, Priority Degree, Alternatives, Attributes
To cite this article
Mingming Hu, Xinmiao Ye, Jibin Lan, Fang Liu, A Possibility Priority Degree Analyzing Process for Multiple Attributes Decision Making Problems, European Business & Management. Vol. 4, No. 2, 2018, pp. 44-54. doi: 10.11648/j.ebm.20180402.11
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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