Long Term Constraint

Long-term constraint optimization focuses on making sequential decisions that minimize costs or maximize rewards while simultaneously satisfying constraints that accumulate over time. Current research emphasizes developing online algorithms, such as those based on exponentially weighted methods, Follow-the-Perturbed-Leader approaches, and bi-level optimization, to handle both convex and non-convex objectives and constraints in various settings, including resource allocation and control systems. These advancements are significant because they enable efficient and robust solutions for real-world problems where long-term resource management, sustainability, or regulatory compliance are crucial, impacting fields like network resource allocation, sustainable energy, and robotics.