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基于遺傳算法的可重入鋼管生產優化調度

Optimal scheduling of steel tube re-entrant lines based on a genetic algorithm

  • 摘要: 在可重入冷拔無縫鋼管生產的計劃和調度中,根據四個條件對工件進行組批,通過規則假設把組批后的批鋼管看作單個加工工件,建立以最后完工時間、交貨期滿意度和機器總負荷為目標的多目標組批排序優化模型,設定其約束條件,采用基于Pareto的混合遺傳算法對模型進行優化求解.通過算例證明該模型的有效性和合理性.

     

    Abstract: In order to make planning and scheduling for cold-drawn seamless steel tube re-entrant lines, workpieces were grouped together according to four conditions, then the grouped steel tubes were taken as one workpiece through the assumption of conditions. The model of multi-objective order-grouping scheduling optimization was studied, where the final completion time, the delivery satisfaction and the total load of machine were concerned. In addition, the constraint conditions were put forward. The Pareto-based hybrid genetic algorithm was used to make the optimal solution of the model. The effectiveness and rationality of the optimization model was proved by an example.

     

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