Knowledge Management System Of Institute of process engineering,CAS
| Robust optimization and stochastic programming approaches for medium-term production scheduling of a large-scale steelmaking continuous casting process under demand uncertainty | |
| Alternative Title | Comput. Chem. Eng. |
| Ye, Yun1; Li, Jie2,3; Li, Zukui2; Tang, Qiuhua1; Xiao, Xin3; Floudas, Christodoulos A.2 | |
| 2014-07-04 | |
| Source Publication | COMPUTERS & CHEMICAL ENGINEERING
 |
| ISSN | 0098-1354 |
| Volume | 66Issue:1Pages:165-185 |
| Abstract | 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.; 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. |
| Keyword | Scheduling Steelmaking Continuous Casting Robust Optimization Two Stage Stochastic Programming Demand Uncertainty |
| Subtype | Article |
| WOS Headings | Science & Technology ; Technology |
| DOI | 10.1016/j.comphemeng.2014.02.028 |
| URL | 查看原文 |
| Indexed By | SCI ; ISTP |
| Language | 英语 |
| WOS Keyword | MULTIPURPOSE BATCH PROCESSES ; CONTINUOUS-TIME FORMULATION ; STEEL PRODUCTION ; PLANT ; FRAMEWORK ; INDUSTRY |
| WOS Research Area | Computer Science ; Engineering |
| WOS Subject | Computer Science, Interdisciplinary Applications ; Engineering, Chemical |
| WOS ID | WOS:000336373400014 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Version | 出版稿 |
| Identifier | http://ir.ipe.ac.cn/handle/122111/11016 |
| Collection | 研究所（批量导入） |
| Affiliation | 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 |
| Recommended Citation 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. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Robust optimization （1417KB） | 限制开放 | CC BY-NC-SA | Application Full Text | |||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment