ICSES Transactions on Neural and Fuzzy Computing

Vol. 2, No. 1, Apr. 2019

Comparison Analysis between DNMA Method and Other MCDM Methods | Original Paper

Xingli Wu a,, Huchang Liao b
a Sichuan University, Chengdu, China
b Sichuan University, Chengdu, China

Highlights and Novelties


1. We introduce the theory of utility value-based multiple criteria decision making methods.

2. We analyze the normalization, aggregation and integration methods in MCDM.

3. We make comparison analysis between DNMA method and other MCDM methods.


Manuscript Abstract
The utility value-based multiple criteria decision making methods have been widely used in practice. They are simple in calculation and easy to understand. The normalization and aggregation are main parts of the utility value-based methods. There are mainly two normalization techniques with different advantages, including the linear normalization and vector normalization, and three types of aggregation approaches with different functions, including the complete compensatory operator, the un-compensatory operator and the incomplete compensatory operator. The double normalization-based multiple aggregation (DNMA) method, as a new member of the utility value-based methods, has taken the advantages of both two normalization techniques and three aggregation approaches. This paper aims to make a comparative analysis between the DNMA method and other representative utility value-based methods, including the TOPSIS, VIKOR and MULTIMOORA.We focus on the normalization, aggregation and integration techniques of these MCDM methods.Their similarity and some differences are pointed out to direct appropriate applications.

Keywords
 Multiple criteria decision making   Utility value-based method   Double normalization-based multiple aggregation method   Comparative analysis   TOPSIS   VIKOR   MULTIMOORA 

Copyright
© Copyright was transferred to International Computer Science and Engineering Society (ICSES) by all the Authors.

Cite this manuscript as
Xingli Wu, Huchang Liao, "Comparison Analysis between DNMA Method and Other MCDM Methods," ICSES Transactions on Neural and Fuzzy Computing (ITNFC), vol. 2, no. 1, pp. 4-10, Apr. 2019.

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