Saddle point problems refer to a class of mathematical optimization problems where the objective function has both a maximum and a minimum value. These problems arise in a variety of fields, including economics, engineering, and game theory. In saddle point problems, the goal is to find a solution that simultaneously maximizes one part of the objective function and minimizes another part. This can be a challenging task, as the optimal solution must balance these conflicting objectives. Saddle point problems can be solved using various optimization techniques, such as convex optimization, game theory, and mixed-integer programming. Researchers are continuously developing new algorithms and methods to efficiently solve saddle point problems in different contexts.