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120 generated benchmark instances for a reconfigurable assembly line scheduling problem. The dataset supports a study proposing a Q-learning-based multi-objective hyper-heuristic algorithm to optimize product sequencing, reconfiguration cost, workload equalization, and logistics leveling. It was authored by Haoyi Zhao and last updated on 2026-05-21.
Data is in XLS format, requiring software that can read Excel files.