Abstract
With fierce market competition and diversification of customer demand, steel industries are currently facing the challenge of a multi-variety, small-batch, and high-quality production mode. In this study, different constraints, optimization objectives and solving algorithms in hot rolling planning (HRP) are summarized. Considering the particularity of the HRP problem, the vehicle routing problem model was modified, and a corresponding algorithm based on the actual hardness and thickness constraints was designed to solve it. The HRP problem is analysed in detail and solved by Python with an actual production dataset. The developed model has been implemented in a large steel plant, and experimental results show the effectiveness of the proposed model.
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