Neutrosophic hyperbolic programming strategy for uncertain multi-objective transportation problem

Abstract

This paper suggests a neutrosophic hyperbolic programming approach based on the hyperbolic membership function to get an efficient solution for an uncertain multi-objective transportation problem where the uncertain normal distribution presents uncertainty. This technique provides flexibility to the decision-maker to select various confidence levels according to his/her own choice and analyze the satisfaction percentage of the obtained optimal compromise solution along with its truth, indeterminacy, and falsity values. In this approach, the parameters are changed from uncertain to crisp by using the inverse measure theorem, and the neutrosophic non-linear hyperbolic membership functions are used to convert the whole model into a non-linear programming problem in a neutrosophic environment. The advantages of our recommended method in real-world applications are effectively illustrated by a numerical illustration. This illustration also makes it easier to compare the results attained using our suggested strategy to those obtained using the methodologies put forward by Uddin et al. (2021) and Miah et al. (2022). Also, MATLAB software (version R2019a,64bit(win64)) is used to develop the code for the solution of this non-linear uncertain multi-objective transportation problem.