Optimización convexa

Optimización convexa is a mathematical method used to find the best solution—or minimum cost—in problems where the functions involved are "convex." Convex functions have a shape like a bowl, meaning any line segment between two points on the curve stays above the curve. This property ensures that any local minimum is also the global minimum, making it easier to identify the best solution reliably. Convex optimization is widely used in areas like finance, engineering, and machine learning to efficiently solve problems such as minimizing costs or errors while satisfying certain constraints.