An improved genetic algorithm for multi-objective painted body storage scheduling problem

Key Points

• Optimized scheduling solutions improve efficiency in painted body storage management.
• The genetic algorithm was evaluated across multiple objective functions, yielding superior performances.
• Observational analysis of storage scenarios demonstrated enhanced resource allocation and minimized delays.
• Further testing in varied environments is needed to validate the approach's adaptability and robustness.