Description: Interval analysis is a mathematical technique used to handle uncertainties in optimization problems. This methodology allows representing uncertain variables through intervals instead of fixed values, providing a more flexible and realistic way to model situations where data may vary. Essentially, interval analysis seeks to identify optimal solutions within a range of possible values, which is particularly useful in contexts where information is incomplete or imprecise. This technique is based on interval theory, which focuses on the study of sets of numbers that are bounded by a minimum and a maximum. By applying interval analysis, researchers and analysts can evaluate how variations in parameters affect the outcome of a model, enabling them to make more informed and robust decisions. Furthermore, this technique is often integrated into optimization algorithms, where the goal is to maximize or minimize an objective function under certain constraints, considering the inherent uncertainty of the data. In summary, interval analysis is a powerful tool in various fields, including engineering, economics, and computer science, as it provides a framework for addressing the complexity and variability of real-world problems.
