炼钢-精炼-连铸生产过程的重调度理论与方法研究

Steelmaking-refining-Continuous Casting (SCC) process is the bottleneck in iron and steel production. There are much uncertainties in the real-world SCC process, which will make the original schedule be worse greatly or even infeasible. Then, SCC rescheduling becomes essential. According to literature retrieval, research on SCC rescheduling is still in its infancy, i.e. research on SCC rescheduling under complex production environments, such as being with reentrant, buffers, encountering several types of disruption simultaneously, new process flow, is still lacking. However, the production environments in the real-world SCC process are indeed complex. This project studies the SCC rescheduling under complex production environments, which consists of the following three main parts. The first is to develop Grey relational analysis and Learning mechanism based MOEA/DD algorithm, which lay the foundation of many-objective MOEA/DD rescheduling methods. The second is to model the SCC rescheduling problems under complex production environments, and further explore domain knowledge, such as complexity, characters of feasible solutions, cast-break eliminating heuristics, neighborhood structures design and their characters, fitness landscape. The third is to devise high-quality MOEA/DD rescheduling methods by developing encoding and decoding methods, fast evaluation techniques for solutions, intelligent search and adaptive selection of neighborhood structures, etc. A serials of research fruits about SCC rescheduling theories and methods would be given, which provides guidance and practicality in the realistic SCC process.

炼钢-精炼-连铸（SCC）生产过程是钢铁生产中的瓶颈。实际生产中有很多不确定性，这使得调度方案的优化性大大降低甚至不可行，必须进行SCC重调度。据文献检索，目前SCC重调度研究还很初步，缺乏针对带回环、带缓冲区、多种不确定事件同时发生、新工艺流程等复杂生产环境下的SCC重调度的研究，然而现实SCC的生产环境是复杂的。本项目对复杂生产环境下的SCC重调度进行研究，包含以下三方面内容：1）设计基于灰关联分析和学习机制的MOEA/DD算法，为研制高维多目标MOEA/DD重调度算法奠定基础；2）对复杂生产环境下的SCC重调度问题进行建模，探索问题的复杂性、可行解特性、消除断浇启发式、邻域结构设计及特性、适应度地形等领域知识；3）通过对编码解码方法、解的快速评价策略、邻域结构的智能搜索与自适应选择等进行研究，研制高性能MOEA/DD重调度算法。给出一批具有指导性和实用性的SCC重调度理论和方法成果。

在钢铁生产过程中，炼钢-精炼-连铸（Steelmaking-refining-Continuous Casting,SCC）是影响总体效率的瓶颈之一。实际生产环境的复杂性导致实际生产中往往存在着多种动态事件，如机器故障、炉次开工时间延迟等，这使得原始调度方案的优化性大大降低甚至不可行，必须进行SCC重调度。总之，高性能的炼钢-精炼-连铸调度和重调度方法可为SCC实际生产过程提供技术支撑，提高生产效率。本项目的研究成果主要包含以下三方面内容：（1）研究了考虑动态事件的炼钢-精炼-连铸重调度理论与方法。提出了求解考虑动态事件的炼钢-精炼-连铸重调度问题的改进帝国竞争算法。提出了求解考虑动态事件和可调加工时间的炼钢-精炼-连铸重调度问题的改进人工蜂群算法、改进候鸟迁徙优化算法。提出了求解考虑动态事件的混合流水车间重调度问题的多启动变邻域下降算法。（2）研究了炼钢-精炼-连铸调度理论与方法。设计了求解炼钢-精炼-连铸调度问题的改进人工蜂群算法、迭代局部搜索算法。设计了求解可调加工时间的炼钢-精炼-连铸调度问题的灰狼优化调度算法。（3）研究了置换流水车间调度方法。提出了求解带准备时间的置换流水车间调度问题的混合算法。本项目共发表/录用论文13篇，其中，8篇SCI源刊（1篇ESI高被引论文）、5篇EI。本项目的研究成果丰富了炼钢-精炼-连铸调度理论与方法、炼钢-精炼-连铸重调度理论与方法，具有科学价值和应用价值。