Abstract: Aircraft noise is one of the critical certification criteria for civil aviation authorities, with high-lift devices being a major contributor to airframe noise during takeoff and landing phases. When deployed, these devices—particularly multi-element slotted flaps and leading-edge slats—generate highly unsteady flow fields characterized by strong shear layers, flow separation, and large-scale vortex shedding in cavity regions, which act as potent aerodynamic noise sources. This study focuses on noise reduction for the canonical 30P30N three-element high-lift configuration, which closely represents practical high-lift systems used in modern transport aircraft. A hybrid computational aeroacoustics framework is employed, combining high-fidelity computational fluid dynamics (CFD) with acoustic analogy theory. Specifically, the Improved Delayed Detached Eddy Simulation (IDDES) approach is utilized to resolve the unsteady turbulent flow over the 30P30N wing at a representative approach condition. The resulting time-accurate surface pressure data on the slat and flap components are then used as input to solve the Ffowcs Williams–Hawkings (FW-H) equation in permeable surface form, enabling accurate prediction of far-field acoustic radiation. To mitigate the dominant slat-cavity noise mechanism, a localized steady jet is introduced along the lower trailing edge of the slat, aimed at disrupting the formation and evolution of large-scale coherent vortices within the slat cove. Building upon this physics-based simulation setup, an efficient optimization framework is developed. A Kriging surrogate model is constructed using a Latin Hypercube Sampling (LHS) design of experiments, with jet velocity and jet angle serving as the two primary design variables. The objective function is defined as the overall sound pressure level (OASPL) at a specified observer location, while the lift coefficient is treated as a hard constraint to ensure that aerodynamic performance is not compromised. A genetic algorithm (GA) is then coupled with the Kriging model to perform constrained single-objective optimization. The results demonstrate that the optimized jet configuration achieves a significant noise reduction of 4 dB in OASPL relative to the baseline clean configuration. Remarkably, this reduction is accompanied by a slight improvement in lift coefficient, indicating that judiciously controlled active flow actuation can simultaneously enhance both acoustic and aerodynamic performance.