Knowledge-driven co-evolutionary algorithm for flexible job shop scheduling problem with consistent sublots

Key Points

• Job shop scheduling optimization showed significant efficiency improvements with a co-evolutionary algorithm, especially in managing sublots.
• A notable enhancement in schedule flexibility was observed, allowing better adaptation to changes in job priorities.
• Assessment using a knowledge-driven approach indicated substantial reductions in job completion times across multiple scheduling scenarios.
• Highlights the potential for enhanced operational performance in manufacturing settings through advanced scheduling techniques.