A self-testing cloud model for multi-criteria group decision making
Abstract
Purpose
The purpose of this paper is to select the best scaling coefficient during the quantitative-qualitative conversion.
Design/methodology/approach
Cloud model can describe the qualitative concept of randomness and fuzziness, achieve uncertain transition between qualitative and quantitative in the field of multi-criteria group decision and has been receiving widespread attention. This paper discusses scale conversion issues of the cloud model when evaluating qualitative information. In order to improve the accuracy of the evaluation on multi-attribute decision problems based on uncertainty of natural linguistic information, this paper proposes a method of self-testing cloud model based on a composite scale (with the exponential scale and the scale as a basis).
Findings
Through experimental verification results show that under composite scale, the best suitable selection of can effectively improve the accuracy and reliability of decision results.
Originality/value
This research presents a new approach to determine the suitable value for coefficient based on uncertain knowledge of natural multi-criteria group decision making, and gives concrete steps and examples. This method has positive significance to improve the quality of qualitative and quantitative conversion based on cloud model.
Keywords
Acknowledgements
The authors would like to thank the research was supported by Recruiting High Level Talent program of the Ningde Normal University (2014Y005), Ningde Bureau of Science and Technology under Grant Number 20150045, School Innovation Team of the Ningde Normal University (2015T011), Education Department of Fujian Province under Project Number JA15556, Project of National College Students Innovation Training (201510398014) and Youth Project of Ningde Normal University (2015Q08).
Citation
Chang, T.-C. and Wang, H. (2016), "A self-testing cloud model for multi-criteria group decision making", Engineering Computations, Vol. 33 No. 6, pp. 1767-1783. https://doi.org/10.1108/EC-08-2015-0258
Publisher
:Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited