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An Effective Approach for the Scheduling of Refining Process with uncertain iterations in Steel-making and Continuous Casting Process

机译:炼钢和连铸过程中不确定迭代的精炼工艺调度的有效方法

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Refining is a high temperature, high energy expenditure and large scale logistics machining process in the steel-making and continuous casting (SCC) production. The refining process is mainly characterized by the time-critical and component-critical design. However, the designed activities are often interlinked and quite uncertain; some of the stages may have to be iterated several times to meet the design criteria if the components of the molten steel do not meet the designed criteria for the casting process and the do not meet the established target dates. So, how to generate a robust and optimal schedule to handle the uncertainties for the refining process in a limited time by a computationally efficient manner is becoming critical for the production of iron and steel. After the seperable problem formulation is created, The stochastic dynamic programming method is adopt to the obtained subproblems which are relaxed by Lagrangian relaxation multipliers, the actual schedule is dynamically constructed based on the dual solution. The method has been tested by using practical data from the Shanghai Bashan steel plant in China and could get near optimal solutions in a limited time; the uncertain number of iterations is effectively handled for the production.
机译:精炼是炼钢和连铸(SCC)生产中的高温,高能耗和大规模物流加工过程。精炼过程的主要特点是对时间要求严格和对部件要求严格的设计。但是,设计的活动通常是相互关联的,并且不确定。如果钢水的成分不符合铸造工艺的设计标准并且不符合既定的目标日期,则某些阶段可能必须重复几次才能达到设计标准。因此,如何以有效的计算方式在有限的时间内生成鲁棒且最佳的时间表以处理精炼过程中的不确定性,对于钢铁的生产至关重要。在创建可分的问题表述之后,对获得的子问题采用随机动态规划方法,这些子问题由拉格朗日松弛乘子进行松弛,并基于对偶解动态构建实际进度表。该方法已经使用来自中国上海巴山钢铁厂的实际数据进行了测试,并且可以在有限的时间内获得最佳解决方案。有效地处理了不确定的迭代次数。

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