Dimensions overall score 8.0

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• The proposed method outperforms traditional heuristics and advanced DRL methods in terms of makespan and pallet changes on both synthetic and real production line datasets.result 90%
• The method achieves a good balance between solution quality and computational cost.result 85%
• A heterogeneous graph network within the DRL framework models the global state by constructing efficient message passing among machines, operations, and buffers.method 90%
• The network focuses on avoiding decisions that may cause frequent pallet changes during long-sequence scheduling.technical 85%
• The approach helps improve buffer utilization and overall decision quality.result 80%
• Current FJSP studies often ignore or idealize practical constraints like limited buffer problems.limitation 85%
• DRL's capacity for state modeling remains limited when handling complex dependencies and long-term constraints.limitation 80%
• The success of the system depends on accurate real-time data from production lines.limitation 75%

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