基于启发式和蚁群算法的厚板热轧生产调度

Jiangtao Xu, Jinliang Ding, Qing-da Chen, Ling Yi
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引用次数: 0

摘要

热轧板坯调度在厚板生产智能制造中起着重要的作用。它面临着多规格、小批量和特色生产模式的挑战。产品规格的大范围波动导致现有方法难以应用。为了解决这一问题,提出了一种基于启发式算法和蚁群算法的平板调度方法。计划问题分为板坯分配和板坯轧制顺序优化两个阶段。在板坯分配阶段,采用从前送中选择合适板坯的策略。然后,结合基于规格跳罚的约束处理策略,设计了一种蚁群算法来解决板坯轧制序列优化问题。进行了计算实验,并通过实际生产数据验证了该方法的有效性。
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Hot Rolling Scheduling of Heavy Plate Production Based on Heuristic and Ant Colony Algorithms
Slab scheduling of hot rolling plays an important role in smart manufactory of heavy plate production. It faces the challenges of multiple specifications, small batch and characteristic mode of production. The wide-range fluctuation of product specifications leads the existing approaches difficult to used. To solve this problem, a novel slab scheduling approach based on heuristic and ant colony algorithms is proposed. The schedule problem is formulated in two stages, namely slab allocation and slab rolling sequence optimization. In the slab allocation stage, the strategy of selecting appropriate slabs from forward delivery is used. Then, an ant colony algorithm combined with a constraints handling strategy based on specification jump penalties is designed to solve the slab rolling sequence optimization problem. The computational experiments are carried out and the results demonstrate the effectiveness by the actual production data.
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