Assessing integrated TOPSIS Model with exponential intuitionistic entropy measure: A case study

Ayasrah, Omar and Faiz, Mohd Turan (2022) Assessing integrated TOPSIS Model with exponential intuitionistic entropy measure: A case study. In: Enabling Industry 4.0 through Advances in Manufacturing and Materials: Selected Articles from iM3F 2021, Malaysia, 20 September 2021 , Virtually hosted by Universiti Malaysia Pahang. pp. 49-57., 1. ISBN 978-981-19-2890-1

[img] Pdf
Restricted to Repository staff only

Download (159kB) | Request a copy


t Solving multi-criteria decision-making (MCDM) problems requires assigning weights to the problem’s criteria, the determination of criteria weights could be subjectively or objectively. Many studies emphasized the effectiveness of using objective techniques to derive criteria weights, like using entropy as a measure of fuzziness of the fuzzy sets to detect criteria weights. Despite that, still this subject under study and debate between researchers. This is due to the importance and effect of the criteria weights on the final results. The proposed MCDM method integrates the TOPSIS approach with the intuitionistic fuzzy entropy measure in exponential form, aiming to have an MCDM method that is simple to be implemented and compensate the need to determining the criteria weights. In this paper, the process of the new MCDM method is introduced, with two practical examples to demonstrate the simplicity of the proposed method, and to prove its effectiveness without the need to determine the attribute weights. At the end of each example, a comparison table is provided to benchmark the generated result from the new method with the results from other comparable methods.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: Intuitionistic fuzzy entropy · Exponential intuitionistic fuzzy entropy · Intuitionistic fuzzy TOPSIS · MCDM
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
T Technology > TJ Mechanical engineering and machinery
Faculty/Division: Institute of Postgraduate Studies
Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User: Ms. Ratna Wilis Haryati Mustapa
Date Deposited: 11 Oct 2022 02:22
Last Modified: 12 Oct 2022 07:19
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item