Modeling and optimization method of slab destination decision-making problem

WANG Cheng; ZHENG Zhong; WANG Yong-zhou; ZHANG Kai-tian

doi:10.13228/j.boyuan.issn0449-749x.20220354

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Iron and Steel ›› 2022, Vol. 57 ›› Issue (12) : 169-178. DOI: 10.13228/j.boyuan.issn0449-749x.20220354

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Modeling and optimization method of slab destination decision-making problem

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Abstract

The connection and coordination of continuous casting-hot rolling interface are of great significance for the efficient and stable operation of the steel manufacturing process. In view of the limitations of the application of the achievements caused by the simplification of the production organization process in the study of the continuous casting-hot rolling interface, an optimization method based on the casting plan and hot rolling unit plan is proposed,which decides on the destination (reheating furnace,soaking pit,slab yard) of the physical slab,and determines the connection mode (direct hot charging,hot charging,cold charging) through the step-by-step matching between the virtual slab and physical slab. In order to maximize the number of direct hot charging slabs and hot charging slabs in the hot rolling unit plan and minimize their transportation time,an integer nonlinear programming model for slab destination decision-making is established by considering constraints such as forced off-line cold charging requirements,equipment buffer capacity limitations,physical slab and virtual slab matching rules,direct hot charging slab and hot charging slab transport time requirements,and necessary transportation time for slab feeding. An improved harmony search algorithm combined with tabu search is designed to solve the model. The integer coding is used to record the destination plan. The decoding is carried out by simulating the process of physical slab feeding and virtual slab matching and charging. The objective function value of the destination plan is counted and the evaluation value is calculated. The local optimization ability of tabu search is used to avoid premature convergence of harmony search,and an improved harmony search algorithm is obtained. The production data of a hot rolled strip production line in an iron and steel enterprise are tested. The results show that the slab destination decision-making model can increase the direct hot charging rate by 10.57%,increase the hot charge rate by 3.58%, and reduce the transportation time of the direct hot charging slab and hot charging slab by 18.84%. Compared with the tabu search and harmony search,the optimal evaluation value of the improved harmony search algorithm can be increased by 6.26% and 4.51% respectively,indicating the effectiveness of the model and algorithm.

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continuous casting-hot rolling interface / hot delivery and hot charging / slab destination decision-making / improved harmony search algorithm / model

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WANG Cheng, ZHENG Zhong, WANG Yong-zhou, et al. Modeling and optimization method of slab destination decision-making problem[J]. Iron and Steel, 2022, 57(12): 169-178 https://doi.org/10.13228/j.boyuan.issn0449-749x.20220354

References

[1] 王新东,常金宝,李杰. 小方坯连铸-轧钢“界面”技术的发展与应用[J]. 钢铁,2020,55(9):125.(WANG Xin-dong,CHANG Jin-bao,LI Jie. Development and application of "Interface" technology of billet continuous casting-rolling[J]. Iron and Steel,2020,55(9):125.)
[2] 殷瑞钰. 关于连铸与轧钢的衔接和匹配问题[J]. 轧钢,1991,8(2):1.(YIN Rui-yu. Cohesion and matching problem of continuous casting and rolling[J]. Steel Rolling,1991,8(2):1.)
[3] 王先勇,王闯,刘彭涛. 基于精准设计的棒线材产能配置模型[J]. 中国冶金,2015,25(5):19.(WANG Xian-yong,WANG Chuang,LIU Peng-tao. Capacity matching model of rod and wire based on precise design principle[J]. China Metallurgy,2015,25(5):19.)
[4] 石鑫越,韩伟刚,郦秀萍,等. 排队论在连铸-轧钢区段加热炉出坯节奏中的应用[J]. 钢铁,2018,53(5):96.(SHI Xin-yue,HAN Wei-gang,LI Xiu-ping,et al. Application of queuing theory in rhythm of billet of CC-rolling section[J]. Iron and Steel,2018,53(5):96.)
[5] 芦永明,贺东风,徐安军,等. 2250 mm热轧生产线加热炉配置及其生产组织探讨[J]. 冶金能源,2011,30(2):18.(LU Yong-ming,HE Dong-feng,XU An-jun,et al. Discussion on reheating furnaces configuration and production organization of 2 250 mm hot rolling line[J]. Energy for Metallurgical Industry,2011,30(2):18.)
[6] 呼万哲,郑忠,龙建宇,等. 中厚板考虑母板和板坯规格不确定性的下料问题建模及求解[J]. 计算机集成制造系统,2017,23(11):2508.(HU Wan-zhe,ZHENG Zhong,LONG Jian-yu,et al. Modeling and solving cutting stock problem considering specification uncertainties of mother plate and slab of medium and heavy plate[J]. Computer Integrated Manufacturing System,2017,23(11):2508.)
[7] 周继程,上官方钦,丁毅,等. 钢铁制造流程“界面”技术与界面能量损失分析[J]. 钢铁,2020,55(12):99.(ZHOU Ji-cheng,SHANGGUAN Fang-qin,DING Yi,et al. Discuss on interface technology and energy loss of main interface in steel manufacturing process[J]. Iron and Steel,2020,55(12):99.)
[8] 秦洁,包薪群,李里,等. 加热炉供热方式对钢坯氧化烧损的影响及控制措施分析[J]. 冶金能源,2022,41(3):32.(QIN Jie,BAO Xin-qun,LI Li,et al. Analysis on influence factors and control measures of oxidation burning loss of heating furnace[J]. Energy for Metallurgical Industry,2022,41(3):32.)
[9] 王建钢,王皓,李人杰,等. 热送裂纹产生机制及生产工艺控制研究[J]. 连铸,2017(2):22.(WANG Jian-gang,WANG Hao,LI Ren-jie,et al. The mechanism and control measures research of hot charging crack[J]. Continuous Casting,2017(2):22.)
[10] 石鑫越,张春霞,郦秀萍,等. 基于排队论的连铸-轧钢区段铸坯出坯节奏分析[J]. 炼钢,2018,34(2):51.(SHI Xin-yue,ZHANG Chun-xia,LI Xiu-ping,et al. Analysis on the rhythm of billet in CC-rolling section based on queuing theory[J]. Steelmaking,2018,34(2):51.)
[11] Dong H,Huang M,Ip W H,et al. Improved variable neighbourhood search for integrated tundish planning in primary steelmaking processes[J]. International Journal of Production Research,2012,50(20):5747.
[12] 郑忠,刘怡,陈开,等. 炼钢-连铸-热轧生产计划编制的统一模型及智能算法[J]. 北京科技大学学报,2013,35(5):687.(ZHENG Zhong,LIU Yi,CHEN Kai,et al. Unified modeling and intelligent algorithm of production planning for the process of steelmaking,continuous casting and hot rolling[J]. Journal of University of Science and Technology Beijing,2013,35(5):687.)
[13] 张旭君,吕志民. 炼铸轧集成计划与调度组批模型及算法[J]. 控制与决策,2013,28(8):1257.(ZHANG Xu-jun,LÜ Zhi-min. Model and solution of integrated batch planning and scheduling forsteelmaking-continuous casting-hot rolling[J]. Control and Decision,2013,28(8):1257.)
[14] 芦永明,徐安军,贺东风,等. 一种有利于提高DHCR比例的热轧批量计划编制方法[J]. 北京科技大学学报. 2011,33(10): 1301.(LU Yong-ming,XU An-jun,HE Dong-feng,et al. Hot-rolling batch planning method available to improve DHCR proportion[J]. Journal of University of Science and Technology Beijing,2011,33(10):1301.)
[15] 宁树实,王伟. 热轧批量计划编制模型及其算法[J]. 系统仿真学报,2007,19(3):691.(NING Shu-shi,WANG Wei. Model and algorithm for hot rolling lot planning[J]. Journal of System Simulation,2007,19(3):691.)
[16] 张春生,李铁克. 炼钢与热轧调度方案动态协调方法研究[J]. 冶金自动化,2016,40(5):19.(ZHANG Chun-sheng,LI Tie-ke. Study on the dynamic coordination between steelmaking-continuous casting scheduling and hot rolling scheduling[J]. Metallurgical Industry Automation,2016,40(5):19.)
[17] 郑忠,王永周,卢义,等. 考虑铸轧协调的炼钢-连铸-热轧一体化生产计划[J]. 钢铁,2020,55(12):107.(ZHENG Zhong,WANG Yong-zhou,LU Yi,et al. Integrated production planning of steelmaking-continuous casting-hot rolling considering coordination between casting and rolling[J]. Iron and Steel,2020,55(12):107.)
[18] JIA S,ZHU J,YANG G,et al. A decomposition-based hierarchical optimization algorithm for hot rolling batch scheduling problem[J]. The International Journal of Advanced Manufacturing Technology,2012,61(5-8):487.
[19] Puttkammer K,Wichmann M G,Spengler T S. A GRASP heuristic for the hot strip mill scheduling problem under consideration of energy consumption[J]. Journal of Business Economics,2016,86(5):537.
[20] TANG L,REN H,YANG Y. Reheat furnace scheduling with energy consideration[J]. International Journal of Production Research,2015,53(6):1642.
[21] 闫祺,李文甲,王稼晨,等. 基于改进差分进化算法的加热炉调度方法[J]. 工程科学学报,2021,43(3):422.(YAN Qi,LI Wen-jia,WANG Jia-chen. Reheat furnace production scheduling based on the improved differential evolution algorithm[J]. Chinese Journal of Engineering,2021,43(3):422.)
[22] TANG L,WANG X. A two-phase heuristic for the production scheduling of heavy plates in steel industry[J]. IEEE Transactions on Control Systems Technology,2010,18(1):104.
[23] TAN Y,ZHOU M,WANG Y,et al. A Hybrid MIP-CP approach to multistage scheduling problem in continuous casting and hot-rolling processes[J]. IEEE Transactions on Automation Science and Engineering,2019,16(4):1860.
[24] Geem Z W,Kim J H,Loganathan G V. A new heuristic optimization algorithm:Harmony search[J]. Simulation,2001,2(2):60.
[25] Glover F. Future paths for integer programming and links to artificial intelligence[J]. Computers and Operations Research,1986,13(5):533.