Solution of intuitionistic fuzzy linear programming problem by dual simplex algorithm and sensitivity analysis

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.

Automated summary

Sensitivity analysis is a crucial method to study the impact of changes in model parameters on the optimal solution, enabling researchers to analyze the behavior of the optimal solution. By using numerical examples and ranking methods, the range within which parameters can vary without affecting the optimality of the solution can be determined.