Robust optimization and stochastic programming approaches for medium-term production scheduling of a large-scale steelmaking continuous casting process under demand uncertainty
Ye, Yun1; Li, Jie2,3; Li, Zukui2; Tang, Qiuhua1; Xiao, Xin3; Floudas, Christodoulos A.2
刊名COMPUTERS & CHEMICAL ENGINEERING
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://WOS:000336373400014
语种英语
WOS记录号WOS:000336373400014
公开日期2014-08-28
内容类型期刊论文
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.
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