Open AccessImplementing the reliability of data information in multi-criteria decision making process based on fuzzy TOPSIS and fuzzy entropy
Author(s) -
Noor Jamal,
Ku Muhammad Naim Ku Khalif,
Mimi Mohaffyza Mohamad
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1988/1/012006
Subject(s) - topsis , ideal solution , data mining , fuzzy logic , entropy (arrow of time) , fuzzy number , computer science , mathematics , mathematical optimization , artificial intelligence , machine learning , fuzzy set , operations research , physics , quantum mechanics , thermodynamics
A multi-criteria decision-making process utilizes real-time data information, which is inherently uncertain and imprecise. To be relevant in the decision-making process, real-time data information must be reliable. Because fuzziness alone is insufficient to solve decision-making problems, measuring the information’s reliability is critical. Z-number, which incorporates both restrictions and reliability in its definition is considered as a powerful tool to depict the imperfect information. In this paper, a new methodology is developed based on fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method and fuzzy entropy for solving the multi-criteria decision-making problems where the weight information for decision makers and criteria is incomplete. The evaluation of the information is represented in the form of linguistic terms and the following calculation is performed using Z-numbers. Fuzzy entropy is applied to determine the weights of the criteria and fuzzy TOPSIS is used to rank the alternatives. An empirical study of subjective well-being of working women is used to demonstrate the proposed methodology.