A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 1 Issue 2
Apr.  2014

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Tianmu Ma, Xiaochuan Luo and Tianyou Chai, "Modeling and Hybrid Optimization of Batching Planning System for Steelmaking-continuous Casting Process," IEEE/CAA J. of Autom. Sinica, vol. 1, no. 2, pp. 113-126, 2014.
Citation: Tianmu Ma, Xiaochuan Luo and Tianyou Chai, "Modeling and Hybrid Optimization of Batching Planning System for Steelmaking-continuous Casting Process," IEEE/CAA J. of Autom. Sinica, vol. 1, no. 2, pp. 113-126, 2014.

Modeling and Hybrid Optimization of Batching Planning System for Steelmaking-continuous Casting Process

Funds:

This work was supported by National Natural Science Foundation of China (69074091, 61174187, 61104174), National Program on Key Basic Research Project (2009CB320601), Program for New Century Excellent Talents in University (NCET-08-0105), 111 Project (B08015).

  • This paper investigates the batching problem for steelmaking and continuous casting production in an iron and steel enterprise. The tasks of this problem are to decide how to select slabs and determine their width, how to group the selected slabs into charges and then group the charges into tundishes, how to determine the sequence of charges in each tundish, and how to group tundishes into casts and determine the sequence of tundishes in each cast. The effective decision on the batching problem can help balance the requirements of the sequential process after steelmaking and continuous casting, reduce production cost, and improve slab quality. We first give the mathematical description of the original problem. Based on the analysis of width, we present a decomposition strategy to divide the model into three sub-models, i.e., charge design model, tundish design model and cast design model, while adding relevant objectives and constraints. According to the characteristics of each sub-model, we present hybrid optimization algorithms separately. Computational experiments show the strategy, models and algorithms can generate satisfactory solutions.

     

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  • [1]
    Ji R G, Lu Y Z. A multi-agent and extremal optimization system for steelmaking-continuous casting-hot strip mill integrated scheduling. In:Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management. Hong Kong:IEEE, 2009. 2365-2369
    [2]
    Li J, Xiao X, Tang Q H, Floudas C A. Production scheduling of a largescale steelmaking continuous casting process via unit-specific eventbased continuous-time models:short-term and medium-term scheduling. Industrial & Engineering Chemistry Research, 2012, 51(2):7300-7319
    [3]
    Tang L X, Wang G S. Decision support system for the batching problems of steelmaking and continuous-casting production. Omega-International Journal of Management Science, 2008, 36(6):976-991
    [4]
    Zhu Dao-Fei, Zheng Zhong, Gao Xiao-Qiang. Intelligent optimizationbased production planning and simulation analysis for steelmaking and continuous casting process. Journal of Iron and Steel Research International, 2010, 17(9):19-24
    [5]
    Dawande M, Kalagnanam J, Lee H S, Reddy C, Siegel S. The slabdesign problem in the steel industry. Interfaces, 2004, 34(3):215-225
    [6]
    Dash S, Kalagnanam J, Reddy C, Song S H. Production design for plate products in the steel industry. IBM Journal of Research and Development, 2007, 51(3-4):345-362
    [7]
    Lee K, Chang S Y, Hong Y S. Continuous slab caster scheduling and
    [8]
    Chang S Y, Chang M R, Hong Y S. A lot grouping algorithm for a continuous slab caster in an integrated steel mill. Production Planning & Control, 2000, 11(4):363-368
    [9]
    Tang L X, Liu G L. A mathematical programming model and solution for scheduling production orders in Shanghai Baoshan Iron and Steel Complex. European Journal of Operational Research, 2007, 182(3):1453-1468
    [10]
    Tang L X, Jiang S J. The charge batching planning problem in steelmaking process using Lagrangian relaxation algorithm. Industrial & Engineering Chemistry Research, 2009, 48(16):7780-7787
    [11]
    Tang L X, Luo J X. A new ILS algorithm for cast planning problem in steel industry. ISIJ International, 2007, 47(3):443-452
    [12]
    Dong H Y, Huang M, Ip W H, Wang X W. On the integrated charge planning with flexible jobs in primary steelmaking processes. International Journal of Production Research, 2010, 48(21):6499-6535
    [13]
    Tang L X, Liu J Y, Rong A Y. A mathematical programming model for scheduling steelmaking-continuous casting production. European Journal of Operational Research, 2000, 120(2):423-435
    [14]
    Pacciarelli D, Pranzo M. Production scheduling in a steelmakingcontinuous casting plant. Computers & Chemical Engineering, 2004, 28(12):2823-2835
    [15]
    Roy R, Adesola B A, Thornton S. Development of a knowledge model for managing schedule disturbance in steel-making. International Journal of Production Research, 2004, 42(18):3975-3994
    [16]
    Missbauer H, Hauber W, Stadler W. A scheduling system for the steelmaking-continuous casting process. A case study from the steelmaking industry. International Journal of Production Research, 2009, 47(15):4147-4172
    [17]
    Lee H S, Haider S W, Morse D V. Primary production scheduling at steelmaking industries. IBM Journal of Research Develop, 1996, 40(2):231-252
    [18]
    Tang L X, Liu J Y, Rong A Y. A review of planning and scheduling systems and methods for integrated steel production. European Journal of Operational Research, 2001, 133(1):1-20
    [19]
    Xie Hai. Improved relative superiority method for ranking interval numbers. Science Technology and Engineering, 2007, 8(2):5983-5987(in Chinese)
    [20]
    Hansen P, Mladenovic N. Variable neighborhood search:principles and applications. European Journal of Operational Research, 2001, 130(3):449-467
    [21]
    Hemmelmayr V, Schmid V, Blum C. Variable neighbourhood search for the variable sized bin packing problem. Computers & Operations Research, 2012, 39(5):1097-1108
    [22]
    Bullnheimer B H, Hartl R F, Strauss R F. An improved ant system algorithm for the vehicle routing problem. Annals of Operations Research, 1999, 89:319-328
    [23]
    Ahmadizar F. A new ant colony algorithm for makespan minimization in permutation flow shops. Computers & Industrial Engineering, 2012, 63(2):355-361
    [24]
    Escario J B, Jimenez J F, Giron-Sierra J M. Optimisation of autonomous ship manoeuvres applying ant colony optimisation metaheuristic. Expert Systems with Applications, 2012, 39(11):10120-10139

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