Deep Q-Network (DQN) Assisted Fruit Fly Optimization Algorithm for Steelmaking-Continuous Casting Scheduling Problems

Driven by accelerated globalization and technological innovation, modern industrial systems have entered an era of transformative growth. Within this context, the steelmaking-continuous casting (SCC) process emerges as the core production phase, where the rationality and efficiency of production scheduling directly determine product quality and throughput. Confronting the limitations of conventional metaheuristic algorithms in solution precision and computational efficiency, this study proposes a novel Deep Q-Network (DQN) assisted Fruit Fly Optimization Algorithm (DQN-FOA), in which the DQN is used to guide the search direction of the FOA. Extensive numerical tests validate the superior optimization performance of the DQN-FOA, including convergence speed and optimization results.