Hyper-heuristic Algorithm based on ε-Greedy for Solving the Online Seru Scheduling Problem *

We address an online seru scheduling problem with the uncertainty of new batch arrivals. First, the decision-making process for online seru scheduling is delineated. Subsequently, drawing on this process, we design three simple and effective scheduling rules that have different advantages. To optimize their inherent benefits, an ε-greedy based hyper-heuristic algorithm is designed to adaptively select the appropriate rule for online seru scheduling. Within this algorithmic framework, the three scheduling rules serve as low-level heuristics, while ε-greedy acts as a high-level strategy. The extensive experiments are conducted to demonstrate the performance of the proposed algorithm.