Variable neighborhood search based multi-objective optimization method for batch scheduling of hot-rolled bars
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摘要: 針對熱軋圓鋼的批量調度問題,考慮實際生產中工藝規程和交貨期對軋制單元連續加工的影響,建立了以最小化設備調整時間、拖期生產懲罰和鋼種跳躍懲罰為優化目標的數學模型,并設計了一種嵌入EDD規則的變鄰域搜索算法.算法首先結合模型的約束特征,采用約束滿足技術生成初始解;根據實際生產需求,將最小化設備調整時間作為主要目標,設計變鄰域搜索算法實現目標優化,其中,運用混合算子構造鄰域結構和局部搜索,并引入模擬退火接受準則來控制迭代過程中產生的新解;同時,為了最小化拖期懲罰和鋼種跳躍懲罰,在求解過程中嵌入了EDD規則以及鋼種排序規則.實驗結果表明,模型和算法是可行且有效的.Abstract: A batch scheduling problem of hot-rolled bars was discussed according to the influences of process conditions and due date on the continuous production of rolling units. A mathematical model with three objectives to minimize the setup time, tardiness penalty and steel grade bounce penalty was constructed, and a method of the variable neighborhood search algorithm embedding the earliest due date first (EDD) rule was proposed to solve the model. In consideration of constraints in the model, an initial solution was generated by constraint satisfaction technology. Then, to meet the actual production needs, a variable neighborhood search method was designed to minimize the setup time, which is considered as a primary objective. In this algorithm, a hybrid operator is applied in sha-king and local search, and the idea of simulated annealing is introduced to take control of the acceptance of new solutions. Meanwhile, in order to minimize the tardiness penalty and the steel grade bounce penalty, the earliest due date first rule and the steel grade sorting rule are applied. Experiment results show that the model and the algorithm are feasible and effective.
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