Flow Shop Scheduling

Flow shop scheduling focuses on optimizing the sequence of jobs through a series of processing stages to minimize metrics like makespan and energy consumption, crucial for efficient manufacturing. Current research emphasizes the development and refinement of metaheuristics, such as genetic algorithms and memetic algorithms, often enhanced by reinforcement learning or incorporating knowledge-based strategies to improve solution quality and convergence speed. These advancements are driven by the need for efficient scheduling in increasingly complex manufacturing environments, including those incorporating parallel batch processing and mass customization, impacting both theoretical understanding and practical applications in various industries.