Citation: | LIU Qian, YANG Jian-ping, WANG Bai-lin, LIU Qing, GAO Shan, LI Hong-hui. Genetic optimization model of steelmaking?continuous casting production scheduling based on the “furnace?caster coordinating” strategy[J]. Chinese Journal of Engineering, 2020, 42(5): 645-653. doi: 10.13374/j.issn2095-9389.2019.08.02.004 |
[1] |
殷瑞鈺. 關于智能化鋼廠的討論——從物理系統一側出發討論鋼廠智能化. 鋼鐵, 2017, 52(6):1
Yin R Y. A discussion on “smart” steel plant——view from physical system side. Iron Steel, 2017, 52(6): 1
|
[2] |
Mattfeld D C, Bierwirth C. An efficient genetic algorithm for job shop scheduling with tardiness objectives. Eur J Oper Res, 2004, 155(3): 616 doi: 10.1016/S0377-2217(03)00016-X
|
[3] |
Sakawa M, Mori T. An efficient genetic algorithm for job-shop scheduling problems with fuzzy processing time and fuzzy duedate. Comput Ind Eng, 1999, 36(2): 325 doi: 10.1016/S0360-8352(99)00135-7
|
[4] |
Fang Y D, Wang F, Wang H. Research of multi-objective optimization study for job shop scheduling problem based on grey ant colony algorithm. Adv Mater Res, 2011, 308-310: 1033 doi: 10.4028/www.scientific.net/AMR.308-310.1033
|
[5] |
Rajendran C, Ziegler H. Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs. Eur J Oper Res, 2004, 155(2): 426 doi: 10.1016/S0377-2217(02)00908-6
|
[6] |
Peng K K, Pan Q K, Zhang B. An improved artificial bee colony algorithm for steelmaking-refining-continuous casting scheduling problem. Chin J Chem Eng, 2018, 26(8): 1727 doi: 10.1016/j.cjche.2018.06.008
|
[7] |
Pan Q K. An effective co-evolutionary artificial bee colony algorithm for steelmaking-continuous casting scheduling. Eur J Oper Res, 2016, 250(3): 702 doi: 10.1016/j.ejor.2015.10.007
|
[8] |
鄭忠, 龍建宇, 高小強, 等. 鋼鐵企業以計劃調度為核心的生產運行控制技術現狀與展望. 計算機集成制造系統, 2014, 20(11):2660
Zheng Z, Long J Y, Gao X Q, et al. Present situation and prospect of production control technology focusing on planning and scheduling in iron and steel enterprise. Comput Integr Manuf Syst, 2014, 20(11): 2660
|
[9] |
Tang L X, Liu J Y, Rong A Y, et al. A review of planning and scheduling systems and methods for integrated steel production. Eur J Oper Res, 2001, 133(1): 1 doi: 10.1016/S0377-2217(00)00240-X
|
[10] |
Murata T, Ishibuchi H, Tanaka H. Multi-objective genetic algorithm and its applications to flowshop scheduling. Comput Ind Eng, 1996, 30(4): 957 doi: 10.1016/0360-8352(96)00045-9
|
[11] |
Ishibuchi H, Murata T. A multi-objective genetic local search algorithm and its application to flowshop scheduling. IEEE Trans Syst Man Cybern Part C (Appl Rev)
|
[12] |
袁帥鵬, 李鐵克, 王柏琳. 多目標煉鋼?連鑄生產調度的改進帶精英策略的快速非支配排序遺傳算法. 計算機集成制造系統, 2019, 25(1):115
Yuan S P, Li T K, Wang B L. Improved fast elitist non-dominated sorting genetic algorithm for multi-objective steelmaking-continuous casting production scheduling. Comput Integr Manuf Syst, 2019, 25(1): 115
|
[13] |
張啟敏, 唐秋華, 鄭鵬, 等. 煉鋼連鑄生產調度問題建模及改進遺傳算法求解. 現代制造工程, 2016, 25(11):50
Zhang Q M, Tang Q H, Zheng P, et al. An improved genetic algorithm and mathematical programming model for scheduling steel-making continuous casting production. Mod Manuf Eng, 2016, 25(11): 50
|
[14] |
汪紅兵, 徐安軍, 姚琳, 等. 應用改進遺傳算法求解煉鋼連鑄生產調度問題. 北京科技大學學報, 2010, 32(9):1232
Wang H B, Xu A J, Yao L, et al. Appling an improved genetic algorithm for solving the production scheduling problem of steelmaking and continuous casting. J Univ Sci Technol Beijing, 2010, 32(9): 1232
|
[15] |
Jian W, Xue Y C, Qian J X. Optimum integrated cast plan for steelmaking-continuous casting production scheduling using improved genetic algorithm // 2nd IEEE International Conference on Industrial Informatics, INDIN'04(2004). Berlin, 2004: 283
|
[16] |
Xue Y C, Wang X, Li S Y. Improved genetic algorithm for integrated steelmaking optimum charge plan. IFAC Proceedings Volumes, 2005, 38(1): 61
|
[17] |
Zhu D F, Zheng Z, Gao X Q. Intelligent optimization-based production planning and simulation analysis for steelmaking and continuous casting process. J Iron Steel Res Int, 2010, 17(9): 19 doi: 10.1016/S1006-706X(10)60136-7
|
[18] |
Thamilselvan R, Balasubramanie P. Integrating genetic algorithm, tabu search and simulated annealing for job shop scheduling problem. Int J Comput Appl, 2012, 48(5): 42
|
[19] |
李鐵克, 蘇志雄. 煉鋼連鑄生產調度問題的兩階段遺傳算法. 中國管理科學, 2009, 17(5):68 doi: 10.3321/j.issn:1003-207X.2009.05.010
Li T K, Su Z X. Two-stage genetic algorithm for SM-CC production scheduling. Chin J Manage Sci, 2009, 17(5): 68 doi: 10.3321/j.issn:1003-207X.2009.05.010
|
[20] |
徐兆俊, 鄭忠, 高小強. 煉鋼連鑄生產調度的優先級策略混合遺傳算法. 控制與決策, 2016, 31(8):1394
Xu Z J, Zheng Z, Gao X Q. HGA combined with priority strategy for production planning of steelmaking-continuous casting. Control Decision, 2016, 31(8): 1394
|
[21] |
劉青, 田乃媛, 殷瑞鈺. 煉鋼廠系統的運行原則與調控策略. 過程工程學報, 2003, 3(2):171 doi: 10.3321/j.issn:1009-606X.2003.02.015
Liu Q, Tian N Y, Yin R Y. Operation principle and control strategy for steelmaking workshop system. Chin J Process Eng, 2003, 3(2): 171 doi: 10.3321/j.issn:1009-606X.2003.02.015
|
[22] |
Wang C, Liu Q, Li Q Y, et al. Optimal charge plan model for steelmaking based on modified partheno-genetic algorithm. Control Theory Appl, 2013, 30(6): 734
|