Mathematics and Statistics Vol. 7(3), pp. 57 - 60
DOI: 10.13189/ms.2019.070301
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Modified Weighted Sum Method for Decisions with Altered Sources of Information

Shahryar Sorooshian 1,*, Yasaman Parsia 2
1 School of Business Economics and Law, University of Gothenburg, Gothenburg, Sweden
2 Earth Resources & Sustainability Centre (ERAS), Universiti Malaysia Pahang, Pahang, Malaysia


Multi Attribute Decision Making (MADM) is an asset to provide solutions for our todays' complex issues and problems. The fact of the matter is that the main source of information in many MADMs is a panel of experts. However, in some cases, there is a possibility of lack of knowledge by the panel to rank or weight one or a few particular criterion/criteria for the decision making. Therefore, the decision maker needs an altered source of information to complete the decision making process. Hence, WSM (Weighted Sum Method) by means of the most popular MADM techniques is selected; and as a prior aim of this article, a modified version of the WSM is proposed as a solution for multiple criteria decision makers by way of a solution for the cases when there is a need for another source of information to rank or weight the particular criterion/criteria. The modified WSM is presented in five stages. The validity, through feasibility, of the modified WSM is tested and verified in a numerical example. Additionally, following this article, future researches could use the same approach for modification of other MADMs to deal with two or more sources of information.

Multi-criteria Decision Making, MADM, WSM, Information

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Shahryar Sorooshian , Yasaman Parsia , "Modified Weighted Sum Method for Decisions with Altered Sources of Information," Mathematics and Statistics, Vol. 7, No. 3, pp. 57 - 60, 2019. DOI: 10.13189/ms.2019.070301.

(b). APA Format:
Shahryar Sorooshian , Yasaman Parsia (2019). Modified Weighted Sum Method for Decisions with Altered Sources of Information. Mathematics and Statistics, 7(3), 57 - 60. DOI: 10.13189/ms.2019.070301.