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Multi-stage and multi-attribute risk group decision-making method based on grey information

Multi-stage and multi-attribute risk group decision-making method based on grey information Purpose – For the multi-stage and multi-attribute risk group decision-making problem, the attribute weight, decision-maker weight and time weight are unknown. The attribute value is grey information. The purpose of this paper is to discuss a decision-making method. Design/methodology/approach – Analysis techniques and the theory about distance degree are used to determine the decision-maker weight within single stage. Grey relational analysis method is applied to determine the attribute weight. Moreover, the uncertainty of time weight and the proximity between the attribute value and positive/negative value are taken into account. A multi-objective optimization model is established based on maximum entropy to obtain time weights, so the comprehensive value is determined. Findings – An example shows the effectiveness and practicability. Originality/value – For a decision-making process, the results are different in different periods. This method is computationally very simple, easily comprehensible. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Grey Systems: Theory and Application Emerald Publishing

Multi-stage and multi-attribute risk group decision-making method based on grey information

Grey Systems: Theory and Application , Volume 5 (2): 12 – Aug 3, 2015

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
2043-9377
DOI
10.1108/GS-01-2015-0002
Publisher site
See Article on Publisher Site

Abstract

Purpose – For the multi-stage and multi-attribute risk group decision-making problem, the attribute weight, decision-maker weight and time weight are unknown. The attribute value is grey information. The purpose of this paper is to discuss a decision-making method. Design/methodology/approach – Analysis techniques and the theory about distance degree are used to determine the decision-maker weight within single stage. Grey relational analysis method is applied to determine the attribute weight. Moreover, the uncertainty of time weight and the proximity between the attribute value and positive/negative value are taken into account. A multi-objective optimization model is established based on maximum entropy to obtain time weights, so the comprehensive value is determined. Findings – An example shows the effectiveness and practicability. Originality/value – For a decision-making process, the results are different in different periods. This method is computationally very simple, easily comprehensible.

Journal

Grey Systems: Theory and ApplicationEmerald Publishing

Published: Aug 3, 2015

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