Linear fractional transportation problem in bipolar fuzzy environment

Abstract

This article proposes a solution methodology for the Linear Fractional Transportation Problem (LFTP) by incorporating bipolar fuzzy sets (BFSs) to accommodate both positive and negative judgmental perspectives. The approach explores Zimmermann's extension within bipolar fuzzy environment to compare outcomes. In this context, the cost function and constraint coefficients are depicted using interval-valued trapezoidal bipolar fuzzy numbers (IVTrBFNs) and defuzzified by (s, t)-cut. The initial approach employs the simplex method and fuzzy optimization method, renowned for its effectiveness in obtaining optimal solutions. In the alternative method, Bipolar fuzzy programming approach (BFPA) is utilized for better outcome. In this method the LFTP is altered to a Multi-Objective Transportation Problem (MOTP), and BFPA extends Zimmermann's technique under suitable positive and negative membership functions, converting MOTP to a one-objective transportation problem (TP) and solved using LINGO software. Supporting this proposed method some theorems are formulated to demonstrate that the most effective solution of the single-objective TP is a Pareto optimal solution for the corresponding MOTP. A quantitative example is provided for better understanding of the proposed BFPA method alongside two other approaches.