Scheduling Heuristic

Scheduling heuristics are algorithms designed to efficiently allocate resources and order tasks to optimize performance metrics like makespan or completion time across diverse applications, from manufacturing and cloud computing to traffic management and wireless communication. Current research emphasizes improving heuristic performance through techniques such as Monte Carlo Tree Search (MCTS), particularly hierarchical variants, and integrating them with reinforcement learning or self-attention mechanisms to handle complex, heterogeneous systems. These advancements aim to address limitations of traditional heuristics, particularly in dynamic environments with unpredictable inputs, leading to more efficient resource utilization and improved system performance in various real-world scenarios.