Multi-objective adaptive large neighborhood search for multi-scenario robust co-scheduling of locks, berths and trucks

Key Points

• Robust co-scheduling leads to efficient resource allocation across multiple scenarios.
• Key evidence shows significant improvement in scheduling efficiency and truck utilization.
• Multi-objective optimization employs adaptive large neighborhood search to minimize delays.
• Highlights the need for further development of advanced scheduling algorithms in logistics.