Sensitivity analysis is designed to study the effect on the optimal solution of changes in model parameters. This analysis is known to be an integral part of any real-life problem solving. This gives a system a dynamic function that enables a researcher to analyze the behavior of the optimal solution as a result of changing the parameters of the model. In this article, postoptimality analysis for changes in objective functions and constraints is presented with suitable numerical illustrations by dual simplex method using magnitude based ranking of triangular intuitionistic fuzzy numbers. The sensitivity range is determined within which the parameters that exist in intuitionistic fuzzy linear programming problem can vary without affecting the optimality of the solution.

Neutrosophic trapezoidal fuzzy multi-numbers (NTFMN) are a specific neutrosophic fuzzy multiset on a real number set that decision makers can use to represent their neutrosophic fuzzy multi-preference information. The occurrences in the NTFMN are several, with the potential of the same or memberships of truth, indeterminacy, and falsehood. Neutrosophic trapezoidal fuzzy multi-numbers(NTFMN) are a type of neutrosophic fuzzy numbers on a real number set that are used to anticipate the solution to multi-criteria decision-making situations. In this study, we begin by defining NTFMN and then develop a set of multiple-criteria decision-making issues with NTFMN alternatives. The expected value method is used to rank neutrosophic trapezoidal fuzzy multi-numbers and choose the best option. Finally, a numerical example is provided to demonstrate the method's practicality and efficiency.