基于遗传算法的可重入钢管生产优化调度

在可重入冷拔无缝钢管生产的计划和调度中,根据四个条件对工件进行组批,通过规则假设把组批后的批钢管看作单个加工工件,建立以最后完工时间、交货期满意度和机器总负荷为目标的多目标组批排序优化模型,设定其约束条件,采用基于Pareto的混合遗传算法对模型进行优化求解.通过算例证明该模型的有效性和合理性.

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

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.