Interior-Point Method

The Interior-Point Method is an algorithm used to solve optimization problems, especially those with constraints, by navigating through the interior of the feasible region rather than along its edges. It gradually moves toward the optimal solution by following a path within the feasible space, using mathematical techniques to efficiently handle large and complex problems. This approach often converges faster than traditional methods, making it valuable in areas like logistics, finance, and engineering where optimal decisions under constraints are crucial.