Volume 2, Issue 4, December 2017, Page: 102-108
Generalized Grey Target Decision Method Based on Decision Makers’ Indifference Attribute Value Preferences
Ma Jinshan, School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo, China
Received: Oct. 18, 2017;       Accepted: Oct. 31, 2017;       Published: Dec. 15, 2017
DOI: 10.11648/j.ajdmkd.20170204.12      View  1506      Downloads  72
In multi-attribute grey target decision making, decision makers may have indifference preferences towards some attribute values such that some superior index values are no different within a small scope or some inferior index values are indifference within a small range. So the target centre domain consisting of some superior values and the target edge domain comprising some inferior values under some attribute were proposed based on the grey target decision theory. Based on the two domains, the Hamming distance of each index value to its target centre domain can be calculated. Following this, the original Hamming distances can be normalized in a linear method individually. Then the decision can be made by the integrated target centre distances considering each attribute’s weight. A case study indicated that the generalized grey target decision method improved easily and combined with other theories can address the decision makers’ indifference attribute value preferences with its concise and simple technique compared with the conventional grey target method, which is superior in handling many feasible alternatives with little difference of superior values or inferior values.
Generalized Grey Target Decision Method, Decision Makers, Indifference Attribute Value Preferences, Target Centre Domain, Target Edge Domain
To cite this article
Ma Jinshan, Generalized Grey Target Decision Method Based on Decision Makers’ Indifference Attribute Value Preferences, American Journal of Data Mining and Knowledge Discovery. Vol. 2, No. 4, 2017, pp. 102-108. doi: 10.11648/j.ajdmkd.20170204.12
Copyright © 2017 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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