Abstract

Several fuzzy approaches have been used for finding the compromise results in the context of “multi-objective transportation problem (MOTP)” with fuzzy parameters. In this work, we have examined a MOTP with “hexagonal fuzzy numbers (HFNs)” as its parameters, i.e., demand, supply and penalties of the problem are mold in HFNs with a new approach developed with the help of a genetic algorithm. Robust ranking is used for the defuzzified value of the hexagonal fuzzy parameters. We have found the BFS (basic feasible solution) of the problem by adopting the zero-point technique. Then the genetic algorithm is used for obtaining the compromising superlative solution by the set of feasible solutions obtained by the zero-point technique of the problem. An algorithm has been developed for the procedure. To figure out the adaptability of the proposed technique, a numerical example has been used.

Author: Kamini, M. K. Sharma, Nitesh Dhiman, Lakshmi Narayan Mishra and Vishnu Narayan Mishra

Received on: December, 2020

Accepted on: August, 2021