A novel Lagrangian relaxation level approach for scheduling steelmaking-refining-continuous casting production | |
Alternative Title | A novel Lagrangian relaxation level approach for scheduling steelmaking-refining-continuous casting production |
Pang Xinfu1; Gao Liang1; Pan Quanke1; Tian Weihua2; Yu Shengping3 | |
2017 | |
Source Publication | JOURNAL OF CENTRAL SOUTH UNIVERSITY
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ISSN | 2095-2899 |
Volume | 24Issue:2Pages:467-477 |
Abstract | A Lagrangian relaxation (LR) approach was presented which is with machine capacity relaxation and operation precedence relaxation for solving a flexible job shop (FJS) scheduling problem from the steelmaking-refining-continuous casting process. Unlike the full optimization of LR problems in traditional LR approaches, the machine capacity relaxation is optimized asymptotically, while the precedence relaxation is optimized approximately due to the NP-hard nature of its LR problem. Because the standard subgradient algorithm (SSA) cannot solve the Lagrangian dual (LD) problem within the partial optimization of LR problem, an effective deflected-conditional approximate subgradient level algorithm (DCASLA) was developed, named as Lagrangian relaxation level approach. The efficiency of the DCASLA is enhanced by a deflected-conditional epsilon-subgradient to weaken the possible zigzagging phenomena. Computational results and comparisons show that the proposed methods improve significantly the efficiency of the LR approach and the DCASLA adopting capacity relaxation strategy performs best among eight methods in terms of solution quality and running time. |
Other Abstract | A Lagrangian relaxation (LR) approach was presented which is with machine capacity relaxation and operation precedence relaxation for solving a flexible job shop (FJS) scheduling problem from the steelmaking-refining-continuous casting process. Unlike the full optimization of LR problems in traditional LR approaches, the machine capacity relaxation is optimized asymptotically, while the precedence relaxation is optimized approximately due to the NP-hard nature of its LR problem. Because the standard subgradient algorithm (SSA) cannot solve the Lagrangian dual (LD) problem within the partial optimization of LR problem, an effective deflected-conditional approximate subgradient level algorithm (DCASLA) was developed, named as Lagrangian relaxation level approach. The efficiency of the DCASLA is enhanced by a deflected-conditional epsilon-subgradient to weaken the possible zigzagging phenomena. Computational results and comparisons show that the proposed methods improve significantly the efficiency of the LR approach and the DCASLA adopting capacity relaxation strategy performs best among eight methods in terms of solution quality and running time. |
Keyword | APPROXIMATE SUBGRADIENT METHODS HYBRID FLOWSHOP ALGORITHM STEEL TIME OPTIMIZATION CONVERGENCE SYSTEM steelmaking-refining-continuous casting Lagrangian relaxation (LR) approximate subgradient optimization |
Indexed By | CSCD |
Language | 英语 |
Funding Project | [National Natural Science Foundation of China] ; [Postdoctoral Science Foundation of China] ; [Liaoning Province Education Administration, China] |
CSCD ID | CSCD:5986060 |
Citation statistics |
Cited Times:7[CSCD]
[CSCD Record]
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Document Type | 期刊论文 |
Identifier | http://ir.imr.ac.cn/handle/321006/142248 |
Collection | 中国科学院金属研究所 |
Affiliation | 1.Huazhong University Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Peoples R China 2.中国科学院金属研究所 3.东北大学 |
Recommended Citation GB/T 7714 | Pang Xinfu,Gao Liang,Pan Quanke,et al. A novel Lagrangian relaxation level approach for scheduling steelmaking-refining-continuous casting production[J]. JOURNAL OF CENTRAL SOUTH UNIVERSITY,2017,24(2):467-477. |
APA | Pang Xinfu,Gao Liang,Pan Quanke,Tian Weihua,&Yu Shengping.(2017).A novel Lagrangian relaxation level approach for scheduling steelmaking-refining-continuous casting production.JOURNAL OF CENTRAL SOUTH UNIVERSITY,24(2),467-477. |
MLA | Pang Xinfu,et al."A novel Lagrangian relaxation level approach for scheduling steelmaking-refining-continuous casting production".JOURNAL OF CENTRAL SOUTH UNIVERSITY 24.2(2017):467-477. |
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