Performance Analysis of Fully Intuitionistic Fuzzy Multi-Objective Multi-Item Solid Fractional Transportation Model

Sultan Almotairi, E. Badr, M. Elsisy, F. Farahat, M. El Sayed
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Abstract

An investigation is conducted in this paper into a performance analysis of fully intuitionistic fuzzy multi-objective multi-item solid fractional transport model (FIF-MMSFTM). It is to be anticipated that the parameters of the conveyance model will be imprecise by virtue of numerous uncontrollable factors. The model under consideration incorporates intuitionistic fuzzy (IF) quantities of shipments, costs and profit coefficients, supplies, demands, and transport. The FIF-MMSFTM that has been devised is transformed into a linear form through a series of operations. The accuracy function and ordering relations of IF sets are then used to reduce the linearized model to a concise multi-objective multi-item solid transportation model (MMSTM). Furthermore, an examination is conducted on several theorems that illustrate the correlation between the FIF-MMSFTM and its corresponding crisp model, which is founded upon linear, hyperbolic, and parabolic membership functions. A numerical example was furnished to showcase the efficacy and feasibility of the suggested methodology. The numerical data acquired indicates that the linear, hyperbolic, and parabolic models require fewer computational resources to achieve the optimal solution. The parabolic model has the greatest number of iterations, in contrast to the hyperbolic model which has the fewest. Additionally, the elapsed run time for the three models is a negligible amount of time: 0.2, 0.15, and 1.37 s, respectively. In conclusion, suggestions for future research are provided.
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全直觉模糊多目标多项目固体分数运输模型的性能分析
本文对全直观模糊多目标多项目固体分数输送模型(FIF-MMSFTM)的性能分析进行了研究。由于众多不可控因素的影响,预计输送模型的参数将是不精确的。所考虑的模型包含了直觉模糊(IF)货运量、成本和利润系数、供应量、需求量和运输量。通过一系列运算,已设计的 FIF-MMSFTM 被转换成线性形式。然后,利用中频集的精度函数和排序关系,将线性化模型简化为简明的多目标多项目固体运输模型(MMSTM)。此外,还对几个定理进行了研究,这些定理说明了基于线性、双曲和抛物线成员函数的 FIF-MMSFTM 模型与其相应的简明模型之间的相关性。为展示所建议方法的有效性和可行性,我们提供了一个数值示例。获得的数值数据表明,线性模型、双曲模型和抛物线模型实现最优解所需的计算资源较少。抛物线模型的迭代次数最多,而双曲线模型的迭代次数最少。此外,三种模型的运行时间分别为 0.2 秒、0.15 秒和 1.37 秒,几乎可以忽略不计。最后,对今后的研究提出了建议。
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