Optimal Assignment

Optimal assignment problems focus on efficiently allocating resources to tasks or agents, aiming to maximize overall performance while considering constraints like cost or time. Current research explores diverse applications, from assigning queries to large language models to optimizing resource allocation in federated learning and ridesharing, employing techniques such as integer programming, reinforcement learning, and multi-armed bandit algorithms. These advancements improve efficiency and resource utilization across various domains, impacting fields like machine learning, operations research, and even biological image analysis. The development of robust and scalable algorithms for optimal assignment continues to be a significant area of investigation.