Description: Post-Optimality Analysis is a technique used in model optimization that is carried out after finding an optimal solution to a problem. Its main objective is to evaluate how changes in model parameters affect the obtained optimal solution. This analysis allows researchers and professionals to understand the robustness of the solution and its sensitivity to variations in initial conditions or input data. Through Post-Optimality Analysis, ranges of variation for parameters that do not alter the optimal solution can be identified, as well as determining the impact of specific changes on the results. This technique is especially valuable in contexts where decisions must be made under uncertainty, as it provides a more comprehensive view of the situation and helps anticipate possible future scenarios. Additionally, Post-Optimality Analysis can be used to make adjustments to the model, further optimizing results and improving decision-making. In summary, it is a crucial tool in model optimization that not only validates the solution found but also explores its behavior under different conditions, resulting in greater confidence in decisions based on mathematical and computational models.
