The multi-stage multi-product batch-sizing problem in the steel industry

The multi-stage multi-product batch-sizing problem in the steel industry
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钢铁行业多阶段多产品批量规模问题

DOI:
10.1016/j.amc.2019.124830
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发表时间:
2020-03
影响因子:
4
通讯作者:
Shuang Qiu
Shuang Qiu
中科院分区:
数学2区
文献类型:
--
作者:
Guoli Liu;Feng Li;Xianyan Yang;Shuang Qiu

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在本文中,我们考虑了钢铁工业中出现的多时期和多类型产品的批量确定问题。在这个问题中,一个产品类型的产品是在满足需求的一系列阶段生产的。每个阶段由一个具有库存容量的在制品存储和一个具有生产率的生产机器组成。它在一个阶段的在制品存储中产生库存成本,并且在第一阶段形成生产批时也会产生安装成本。问题是确定每一个生产批次在每一个周期的形成,使总成本的设置和库存是最小的。针对该问题,我们首先给出了一个混合整数二次规划模型,然后给出了一些最优性性质。基于所提出的性质,我们设计了一个最优算法来在多项式时间内解决问题。最后,我们报告了混合整数二次规划模型的性能和基于实际生产数据的优化算法。计算结果验证了优化算法的可靠性和有效性。
In this paper, we consider a batch-sizing problem with multiple periods and multiple types of products that arises in the steel industry. In this problem, products of a product type are produced in series of stages to fulfill the demand. Each stage consists of a work-in-process storage with inventory capacity and a production machine with a production rate. It incurs an inventory cost in the work-in-process storage of a stage, and also incurs a setup cost whenever a production batch is formed in the first stage. The problem is to determine the formation of each production batch in each period such that the total cost of setup and inventory is minimized. For the problem, we first provide a mixed-integer quadratic programming model and then propose some optimality properties. Based on the proposed properties, we design an optimal algorithm to solve the problem in polynomial time. Finally, we report the performances of the mixed-integer quadratic programming model and the optimal algorithm based on actual production data. The computational results confirm the reliability and validity of the optimal algorithm.
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