Yazar "Shah, Syed Muhammad Umer" seçeneğine göre listele

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    An extended multi-objective transportation model based on Fermatean fuzzy sets
    (Springer, 2023) Akram, Muhammad; Shahzadi, Sundas; Shah, Syed Muhammad Umer; Allahviranloo, Tofigh
    Fermatean fuzzy sets are a more efficient, flexible, and general model for dealing with uncertainty as compared to Pythagorean fuzzy sets. The multi-objective transportation problem in a Fermatean fuzzy setting is examined in this study. Due to the volatility of competitive marketplaces, transportation costs, supply and demand factors are not always reliable. These parameters are regarded as triangular Fermatean fuzzy numbers in this article. The multi-objective transportation problem is addressed using a novel compromise approach based on the ordering of these triangular Fermatean fuzzy numbers. Also, the proposed solution procedure is used to solve a real-world problem in order to show how useful it is. Lastly, the outcomes of the Fermatean fuzzy multi-objective transportation problem are used to illustrate the benefits of the proposed method over previous methods.
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    A fully Fermatean fuzzy multi-objective transportation model using an extended DEA technique
    (Springernature, 2023) Akram, Muhammad; Shahzadi, Sundas; Shah, Syed Muhammad Umer; Allahviranloo, Tofigh
    A mathematical technique called data envelope analysis is used to determine the relative efficiency of decision-making units (DMU) with numerous inputs and outputs. Compared to other DMUs, it determines how efficient the DMU is at delivering a specific level of output based on the amount of input it uses. The transportation problem is a linear programming problem for reducing the net transportation cost or maximizing the net transportation profit of moving goods from a number of sources to a number of destinations. In this manuscript, a multi-objective transportation problem is examined in which all the parameters, such as transportation cost, supply, and demand are uncertain with hesitancy and triangular Fermatean fuzzy numbers are used to represent these uncertain parameters. Using Fermatean fuzzy data envelope analysis, a new technique for determining the common set of weights is presented. The fully Fermatean fuzzy multi-objective transportation problem is then solved using a novel data envelopment analysis-based approach. To this end, two different Fermatean fuzzy efficiency scores are derived, first by considering the sources as targets and changing the destinations, and second by considering the destinations as targets and changing the sources. Next, a unique Fermatean fuzzy relative efficiency is determined for each arc by combining these two different Fermatean fuzzy efficiency scores. As a result, a single-objective Fermatean fuzzy transportation problem is constructed, which can be solved using existing techniques. A numerical illustration is provided to support the suggested methodology, and the performance of the proposed method is compared with an existing technique