Robust optimization and stochastic programming approaches for medium-term production scheduling of a large-scale steelmaking continuous casting process under demand uncertainty
文献类型：期刊论文
| 作者 | Ye, Yun1; Li, Jie2,3; Li, Zukui2; Tang, Qiuhua1; Xiao, Xin3; Floudas, Christodoulos A.2 |
| 刊名 | COMPUTERS & CHEMICAL ENGINEERING
 |
| 出版日期 | 2014-07-04 |
| 卷号 | 66期号:1页码:165-185 |
| 关键词 | Scheduling Steelmaking Continuous casting Robust optimization Two stage stochastic programming Demand uncertainty |
| ISSN号 | 0098-1354 |
| 其他题名 | Comput. Chem. Eng. |
| 中文摘要 | Scheduling of steelmaking-continuous casting (SCC) processes is of major importance in iron and steel operations since it is often a bottleneck in iron and steel production. In practice, uncertainties are unavoidable and include demand fluctuations, processing time uncertainty, and equipment malfunction. In the presence of these uncertainties, an optimal schedule generated using nominal parameter values may often be suboptimal or even become infeasible. In this paper, we introduce robust optimization and stochastic programming approaches for addressing demand uncertainty in steelmaking continuous casting operations. In the robust optimization framework, a deterministic robust counterpart optimization model is introduced to guarantee that the production schedule remains feasible for the varying demands. Also, a two-stage scenario based stochastic programming framework is investigated for the scheduling of steelmaking and continuous operations under demand uncertainty. To make the resulting stochastic programming problem computationally tractable, a scenario reduction method has been applied to reduce the number of scenarios to a small set of representative realizations. Results from both the robust optimization and stochastic programming methods demonstrate robustness under demand uncertainty and that the robust optimization-based solution is of comparable quality to the two-stage stochastic programming based solution. (C) 2014 Elsevier Ltd. All rights reserved. |
| 英文摘要 | Scheduling of steelmaking-continuous casting (SCC) processes is of major importance in iron and steel operations since it is often a bottleneck in iron and steel production. In practice, uncertainties are unavoidable and include demand fluctuations, processing time uncertainty, and equipment malfunction. In the presence of these uncertainties, an optimal schedule generated using nominal parameter values may often be suboptimal or even become infeasible. In this paper, we introduce robust optimization and stochastic programming approaches for addressing demand uncertainty in steelmaking continuous casting operations. In the robust optimization framework, a deterministic robust counterpart optimization model is introduced to guarantee that the production schedule remains feasible for the varying demands. Also, a two-stage scenario based stochastic programming framework is investigated for the scheduling of steelmaking and continuous operations under demand uncertainty. To make the resulting stochastic programming problem computationally tractable, a scenario reduction method has been applied to reduce the number of scenarios to a small set of representative realizations. Results from both the robust optimization and stochastic programming methods demonstrate robustness under demand uncertainty and that the robust optimization-based solution is of comparable quality to the two-stage stochastic programming based solution. (C) 2014 Elsevier Ltd. All rights reserved. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Interdisciplinary Applications ; Engineering, Chemical |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | MULTIPURPOSE BATCH PROCESSES ; CONTINUOUS-TIME FORMULATION ; STEEL PRODUCTION ; PLANT ; FRAMEWORK ; INDUSTRY |
| 收录类别 | SCI ; ISTP |
| 原文出处 | |
| 语种 | 英语 |
| WOS记录号 | WOS:000336373400014 |
| 公开日期 | 2014-08-28 |
| 版本 | 出版稿 |
| 源URL | [http://ir.ipe.ac.cn/handle/122111/11016]  |
| 专题 | 过程工程研究所_研究所（批量导入） |
| 作者单位 | 1.Wuhan Univ Sci & Technol, Dept Ind Engn, Wuhan, Hubei, Peoples R China 2.Princeton Univ, Dept Chem & Biol Engn, Princeton, NJ 08540 USA 3.Inst Proc Engn, State Key Lab Multiphase Complex Syst, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ye, Yun,Li, Jie,Li, Zukui,et al. Robust optimization and stochastic programming approaches for medium-term production scheduling of a large-scale steelmaking continuous casting process under demand uncertainty[J]. COMPUTERS & CHEMICAL ENGINEERING,2014,66(1):165-185. |
| APA | Ye, Yun,Li, Jie,Li, Zukui,Tang, Qiuhua,Xiao, Xin,&Floudas, Christodoulos A..(2014).Robust optimization and stochastic programming approaches for medium-term production scheduling of a large-scale steelmaking continuous casting process under demand uncertainty.COMPUTERS & CHEMICAL ENGINEERING,66(1),165-185. |
| MLA | Ye, Yun,et al."Robust optimization and stochastic programming approaches for medium-term production scheduling of a large-scale steelmaking continuous casting process under demand uncertainty".COMPUTERS & CHEMICAL ENGINEERING 66.1(2014):165-185. |
入库方式： OAI收割
来源：过程工程研究所
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