Development of hybrid evolutionary algorithms for production scheduling of hot strip mill
Development of hybrid evolutionary algorithms for production scheduling of hot strip mill
复制标题
热轧带钢生产调度混合进化算法的开发
DOI：
10.1016/j.cor.2011.04.009
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发表时间：
2012-02-01
影响因子：
4.6
通讯作者：
Pan, Chang-Chun
中科院分区：
文献类型：
--
作者：
Chen, Yu-Wang;Lu, Yong-Zai;Pan, Chang-Chun
热连轧机是钢铁厂最重要的生产线之一，它从板坯中生产热轧产品。高速加工调度的目的是构造一个滚动序列，在约束条件下优化一组给定的标准。由于生产过程建模和轧制顺序优化的复杂性，热轧生产调度是一个具有挑战性的课题。本文首先介绍了高速加工的生产过程和要求，然后回顾了高速加工调度问题的建模和优化研究。根据热轧生产的实际要求，建立了数学模型来描述两个重要的调度子任务：（1）选择制造订单子集和（2）从所选择的制造订单中生成最佳轧制顺序。在此基础上，提出了一种基于遗传算法和极值优化的混合进化算法来求解高速加工调度问题。工业数据的计算结果表明，所提出的高速加工调度解决方案可以应用于实际中，提供令人满意的性能。(C)2011爱思唯尔有限公司版权所有。
A hot strip mill (HSM) produces hot rolled products from steel slabs, and is one of the most important production lines in a steel plant. The aim of HSM scheduling is to construct a rolling sequence that optimizes a set of given criteria under constraints. Due to the complexity in modeling the production process and optimizing the rolling sequence, the HSM scheduling is a challenging task for hot rolling production schedulers. This paper first introduces the HSM production process and requirements, and then reviews previous research on the modeling and optimization of the HSM scheduling problem. According to the practical requirements of hot rolling production, a mathematical model is formulated to describe two important scheduling sub-tasks: (1) selecting a subset of manufacturing orders and (2) generating an optimal rolling sequence from the selected manufacturing orders. Further, hybrid evolutionary algorithms with integration of genetic algorithm (GA) and extremal optimization (EO) are proposed to solve the HSM scheduling problem. Computational results on industrial data show that the proposed HSM scheduling solution can be applied in practice to provide satisfactory performance. (C) 2011 Elsevier Ltd. All rights reserved.