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<p>In modern decision-making environments, managing uncertainty and time-dependent preferences is a critical challenge. We in this paper introduces the concept of Fractional Fuzzy Tensor (FFT), an innovative structure that integrates fuzzy logic, tensor theory, and fractional calculus to capture multi-dimensional uncertainty with memory. A novel FFT-TOPSIS model is developed to address dynamic multi-criteria decision-making (MCDM) problems. The model is applied to smartphone and fitness tracker selection problems to illustrate its efficacy. Results reveal the impact of fractional evolution on decision rankings, showcasing the robustness and adaptability of the proposed method.</p>

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Fractional Fuzzy Tensor: A New Approach with Application in Smartphone Selection and Fitness Tracker Selection Using TOPSIS Method

  • 期刊论文

  • 发表日期：

    2025年9月27日

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  • Muhammad Bilal

摘要

In modern decision-making environments, managing uncertainty and time-dependent preferences is a critical challenge. We in this paper introduces the concept of Fractional Fuzzy Tensor (FFT), an innovative structure that integrates fuzzy logic, tensor theory, and fractional calculus to capture multi-dimensional uncertainty with memory. A novel FFT-TOPSIS model is developed to address dynamic multi-criteria decision-making (MCDM) problems. The model is applied to smartphone and fitness tracker selection problems to illustrate its efficacy. Results reveal the impact of fractional evolution on decision rankings, showcasing the robustness and adaptability of the proposed method.