A Novel Ranking Approach for Transportation Problem under Bipolar Fuzzy Environment

This paper formulates a transportation problem where all parameters are represented as bipolar fuzzy numbers (BFNs), reflecting uncertainties due to market fluctuations impacting transportation costs, supply, and demand.BFNs provide a more realistic representation by analysing positive and negative membership, which distinguishes them from traditional fuzzy numbers.This research aims to minimise the transportation cost for various commodities within a transportation problem framework using BFNs.The proposed methodology introduces a novel ranking technique for solving the bipolar fuzzy transportation problem (BFTP), in which the cost supply and demand parameters are expressed as BFNs.The efficiency of the proposed ranking function over other existing ranking functions is also exhibited.An algorithm is presented to describe the solution methodology for BFTP.A numerical example is provided to demonstrate the practical implementation and effectiveness of the proposed method in solving transportation problems under uncertainty represented by BFNs.The study concludes with a discussion of the findings and outlines future avenues for research.