【作者】 刘洋；

【导师】 刘民；

【作者基本信息】 清华大学 ， 控制科学与工程， 2009， 硕士

【摘要】 炼钢-连铸是钢铁生产过程中的重要阶段,实现炼钢-连铸过程的优化调度对提高生产效率和产品质量、降低能耗/物耗、降低生产成本等具有重要作用。同时,炼钢-连铸生产调度是一类重要的复杂调度问题,其具有约束复杂、不确定动态事件多、对调度算法实时性要求高等复杂性,研究炼钢-连铸生产调度问题具有重要的理论意义和实用价值。本文以提高生产效率、降低能耗/物耗为主要目标,研究了炼钢-连铸生产过程的静态调度问题和动态调度问题。论文所做的主要工作如下:本文首先研究了以最小化完工时间和最小化加权等待时间为调度目标、具有强约束特点的炼钢-连铸静态调度问题。在对该类调度问题进行模型描述的基础上,将迭代式分解、预测机制与差分进化算法相结合,提出了一种基于差分进化和迭代式分解的调度算法,并进行了编程实现。其中,采用差分进化算法对连铸机分派方案及各浇次的加工优先级进行全局优化,并将基于预测机制的迭代式分解算法用于上述差分进化的解码过程,以对上述调度问题进行高效的局部优化。然后针对炼钢-连铸生产过程动态调度问题,在对调度相关动态事件进行分类的基础上,提出了炼钢-连铸生产过程动态调度问题解决方案。其中,根据动态事件的类别及扰动大小采用不同的动态调度算法——动态调整算法和重调度算法来求解该类动态调度问题。其中,动态调整算法主要针对具有较小扰动的动态事件,该类算法采用基于预测机制的迭代式分解算法,并融合相关调度专家经验进行动态调度;重调度算法主要针对具有较大扰动的动态事件,该类算法采用基于差分进化和迭代式分解的调度方法进行重调度,以实现全局动态调度。同时,基于上述动态调度问题解决方案,分别针对钢水质量不达标动态事件和设备故障动态事件两类常见的炼钢-连铸调度相关动态事件,提出了两种动态调度算法并进行了编程实现。数值计算结果表明本文所提出的基于差分进化和迭代式分解的炼钢-连铸调度算法是有效的。更多还原

【Abstract】 Steelmaking and continuous casting (SCC) is an important stage in the whole iron and steel production process, and the scheduling of SCC is essential for improving production efficiency and production quality, decreasing energy/material consumption and reducing production cost. Meanwhile, the SCC scheduling problem is a kind of complex scheduling problem, which is characterized as complex constraints, large number of dynamic events and high requirements for real-time. Therefore, the study of the SCC scheduling problem is of great theoretical significance and practical value. To increase production efficiency and reduce material consumption and energy consumption, this dissertation studies the SCC static scheduling problem and SCC dynamic scheduling problem. The main work of this dissertation is as follows.This paper studies the SCC static scheduling problem with the scheduling objective of minimizing the completion time and the weighted waiting time. On the basis of model description of this kind of scheduling problem, this paper proposes and realizes a scheduling algorithm (a scheduling Algorithm based on Differential evolution and Iterative decomposition, ADI) that combines problem decomposition, prediction mechanism and differential evolution algorithm (DE). In the proposed ADI, the DE algorithm is used for the global optimization of machine assignment policies and the processing priority levels of casts, and an iterative decomposition algorithm based on prediction mechanism (IDP) is designed as the decoding process of differential evolution algorithm for efficient exploitation.For the SCC dynamic scheduling problem, this paper proposes a solution framework based on the classification of dynamic events related to the SCC scheduling problem. In the solution framework, different dynamic scheduling algorithms are employed for different categories of dynamic events as well as their disturbance levels. These dynamic algorithms include dynamic adjustment algorithms and rescheduling algorithms. Based on the original scheduling schemes and IDP combined with the experts’experience, the dynamic adjustment algorithms are employed for the scheduling related dynamic events with a small disturbance level. And based on ADI, the rescheduling algorithms are employed for the dynamic events with large disturbance levels to realize global optimization of the dynamic scheduling problem. Meanwhile, considering that the dynamic events of poor quality of molten steel and equipment fault are two types of common scheduling related dynamic events in SCC process, this paper proposes and realizes two dynamic scheduling algorithms respectively based on the solution framework for the SCC dynamic scheduling problem mentioned above.Numerical computations show that the proposed algorithms in this paper are effective for the SCC scheduling problem.更多还原