Capacity Optimization

Capacity optimization focuses on efficiently allocating limited resources to maximize performance, addressing challenges across diverse fields like transportation, telecommunications, and resource allocation problems. Current research emphasizes developing sophisticated models, including game-theoretic approaches, machine learning algorithms (like multi-objective proximal policy optimization), and advanced statistical methods, to optimize capacity under various constraints and objectives (e.g., minimizing cost, maximizing throughput, or achieving stable matchings). These advancements have significant implications for improving efficiency and decision-making in various sectors, from optimizing air cargo logistics and toll lane systems to enhancing wireless network coverage and capacity in next-generation communication technologies.