Advanced Logarithmic Aggregation Operators for Enhanced Decision-Making in Uncertain Environments
Journal Title: International Journal of Knowledge and Innovation Studies - Year 2024, Vol 2, Issue 2
Abstract
This study introduces logarithmic operations tailored to intuitionistic fuzzy sets (IFSs) aimed at mitigating uncertainty in decision-making processes. Through logarithmic transformations, the membership and non-membership degrees are effectively scaled, thereby enhancing interpretability and facilitating the assessment of uncertainty. Advanced logarithmic aggregation operators have been developed, specifically the Induced Confidence Logarithmic Intuitionistic Fuzzy Einstein Ordered Weighted Geometric Aggregation (ICLIFEOWGA) operator and the Induced Confidence Logarithmic Intuitionistic Fuzzy Einstein Hybrid Geometric Aggregation (ICLIFEHGA) operator. These operators serve as versatile tools, providing robust frameworks for integrating diverse information sources in decision-making and assessment processes. The versatility of the operators is demonstrated through their application across various industries and domains, where they support the integration of multiple criteria in complex decision-making scenarios. An algorithm for the decision-making process is presented, and the effectiveness and efficiency of the proposed techniques are illustrated through a case study on laptop selection.
Authors and Affiliations
Quaid Iqbal, Shazia Kalsoom
Keywords
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- EP ID EP744653
- DOI https://doi.org/10.56578/ijkis020201
- Views 33
- Downloads 1
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