Interactive Pythagorean-hesitant fuzzy computational algorithm for multiobjective transportation problem under uncertainty
Ahmad Yusuf Adhami, Firoz Ahmad
Abstract
Transportation problems inherently involve uncertainty in real life. The uncertain framework for optimization of transportation models depends on various aspects. Therefore the effective modeling and optimization configuration is needed to solve such transportation problems. In this study, we have considered a multiobjective transportation problem with fuzzy parameters and developed a new Pythagorean-hesitant fuzzy computational algorithm to solve the problem under uncertainty. The proposed approach is based on Pythagorean-hesitant fuzzy decision set which captures a set of possible values for membership and non-membership degrees of each objective function under the Pythagorean-hesitant fuzzy environment. To show the applicability and validity of the proposed approach a numerical example has been presented. The efficiency performance of the proposed approach has also been discussed along with the comparative study with other existing approaches.