A new method to determine the Fermatean fuzzy optimal solution of transportation problems

Abstract

Transportation Problems (TP) have multiple applications in supply chain management to reduce costs. Efficient methods have been developed to address TP when all factors, including supply, demand, and unit transportation costs, are precisely known. However, due to uncertainty in practical applications, it is necessary to study TP in an uncertain environment. In this paper, we define the Trapezoidal Fermatean Fuzzy Number (TrFFN) and its arithmetic operations. Then we introduce a new approach to solve TP, where transportation cost, supply, and demand are treated as TrFFN, and we call it Fermatean Fuzzy TP (FFTP). We illustrate the feasibility and superiority of this method with two application examples, and compare the performance of this method with existing methods. Furthermore, the advantages of the proposed method over existing methods are described to address TP in uncertain environments.

Optimal Bounds for Fully Fuzzy Transportation Problems: A Parametric Approach

“…Das, S.K [19] addressed triangular fuzzy programming problem, contributing to the theoretical foundation of fuzzy optimization. Akram et al, [20] explored fermatian fuzzy optimal solutions for transportation problems, adding another layer of experience to the fuzzy transportation solving environment. Among all those work our approach is different.…”