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Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making

Authors:

Ying-Ming Wang,

Ying LuoAuthors Info & Claims

Mathematical and Computer Modelling: An International Journal, Volume 51, Issue 1-2

Pages 1 - 12

https://doi.org/10.1016/j.mcm.2009.07.016

Published: 01 January 2010 Publication History

Abstract

This paper proposes a correlation coefficient (CC) and standard deviation (SD) integrated approach for determining the weights of attributes in multiple attribute decision making (MADM) and a global sensitivity analysis to the weights determined. The CCSD integrated approach determines the weights of attributes by considering SD of each attribute and their CCs with the overall assessment of decision alternatives, where CCs are determined by removing each attribute from the overall assessment of decision alternatives. If the CC for an attribute turns out to be very high, then the removal of this attribute has little effect on decision making; otherwise, the attribute should be given an important weight. The global sensitivity analysis to the weights of attributes is proposed to ensure the stability of the best decision alternative or alternative ranking. A numerical example about the economic benefit assessment of the industrial economy of China is investigated to illustrate the potential applications of the CCSD method in determining the weights of attributes. Comparisons with existing weight generation methods are also discussed.

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cover image Mathematical and Computer Modelling: An International Journal

Mathematical and Computer Modelling: An International Journal Volume 51, Issue 1-2

January, 2010

138 pages

ISSN:0895-7177

Issue’s Table of Contents

Copyright © Elsevier Ltd © 2009.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 January 2010

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https://dl.acm.org/doi/10.3233/JIFS-230485
Cheng RFan JWu MSeiti H(2024)A dual-level multi-attribute group decision-making model considering interaction factors based on CCSD and MARCOS methods with R-numbersExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.122839243:COnline publication date: 25-Jun-2024
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