Constrained Problem

Constrained problems, encompassing optimization tasks with limitations on feasible solutions, are a central focus in diverse fields like robotics, machine learning, and operations research. Current research emphasizes developing efficient algorithms, such as augmented Lagrangian methods and evolutionary strategies, to solve these problems, particularly focusing on improving convergence rates and handling complex constraints (e.g., nonlinear, non-convex). These advancements are crucial for enabling safe and effective deployment of autonomous systems and improving the performance of optimization-based techniques across numerous applications, including those involving reinforcement learning and optimal transport.