| Peer-Reviewed

Studying on a Genetic-Simulation Optimization Algorithm Method for Steel Crane Scheduling Problem

Received: 6 December 2016     Published: 7 December 2016
Views:       Downloads:
Abstract

For solving crane scheduling problem in steelmaking-continuous casting process, a hybrid method of integrating genetic algorithm and simulation was formulated to minimize the operation time of tasks by considering full ladles, empty ladles and auxiliary tasks as transportation tasks. The crane selected sequence was designed as chromosome coding. The initial population was generated by employing the crane selection rules in the simulation model, and then evolved optimized by using the genetic operations such as selection, crossover and mutation. The chromosome is evaluated through generating a feasible crane schedule by employing the attribute updating rules and collision eliminating rules in the simulation model. The new crane scheduling could be generated through simulation model based on the new species. Therefore, more excellent individuals will be produced along with the evolutionary process. Thus a better crane scheduling scheme could be obtained finally. In the process of initialization, the high quality initial population was generated in the simulation model. In the iterative process, simulation model also could generate the feasible crane scheduling schemes based on the given cranes selection sequence. To validate this model, experiments were conducted by using the production data in the casting span of a steel plant. The results demonstrate the feasibility and efficiency of this method, which provides a useful tool for crane scheduling in actual production.

Published in Science Innovation (Volume 4, Issue 6)
DOI 10.11648/j.si.20160406.17
Page(s) 283-289
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Crane Scheduling, Simulation Model, Genetic Algorithm, Simulation Rules

References
[1] 刘青,田乃媛,王英群,等.天车调度在优化钢厂物流管制中的重要作用[J].北京科技大学学报,1998(1):36-40。
[2] Jalilvand-Nejad A, Fattahi P. A mathematical model and genetic algorithm to cyclic flexible job shop scheduling problem [J]. Journal of Intelligent Manufacturing, 2013, 26 (6): 1-14.
[3] Ng W C. Crane scheduling in container yards with inter-crane interference [J]. European Journal of Operational Research, 2005, 164 (1): 64-78.
[4] Li W, Wu Y, Goh M. Discrete Time Model and Algorithms for Container Yard Crane Scheduling [J]. European Journal of Operational Research, 2009, 198 (1): 165-172.
[5] Wu Y, Li W, Petering M E H, et al. Scheduling Multiple Yard Cranes with Crane Interference and Safety Distance Requirement [J]. Transportation Science, 2015, 49 (4).
[6] Tanizaki T, Tamura T, Sakai H, et al. A heuristic scheduling algorithm for steel making process with crane handling [J]. Journal of the Operations Research Society of Japan, 2006, 3 (3): 188-201.
[7] De l Vecchio C, Barbarisi O, Parisio A. Hybrid Model for Crane Scheduling [J]. 2008.
[8] Liu P, Tang L X. The refining scheduling problem with crane non-collision constraint in steelmaking process[C]// Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on. IEEE, 2008: 536-541.
[9] 何明,唐秋华,王盛龙.炼钢-连铸天车调度规则设计与评价[J].机械设计与制造,2012,(9):257-259。
[10] 王旭,刘诗新,王佳.求解具有时空约束的天车调度问题Memetic算法[J].东北大学学报(自然科学版),2014,35(2):190-194。
[11] 郑忠,周超,陈开.基于免疫遗传算法的车间天车调度仿真模型[J].系统工程理论与实践,2013,33(1):223-229。
[12] 刘设,王世杰,臧鹏飞,等.重型机械加工车间天车调度问题过程仿真与优化[J].机械设计与制造,2016(8)。
[13] 朱道飞,王华,王建军,等.基于Petri网和UML的钢厂天车调度系统仿真[J].昆明理工大学学报(自然科学版),2013,38(3):5-11。
[14] 赵宁,杜彦华,董绍华,等.基于循环仿真的钢铁板坯库天车作业优化[J].系统工程理论与实践,2012,32(12):2825-2830。
Cite This Article
  • APA Style

    Gao Xiaoqiang, Li Pan, Zheng Zhong, Jiang Shenglong, You Xiao. (2016). Studying on a Genetic-Simulation Optimization Algorithm Method for Steel Crane Scheduling Problem. Science Innovation, 4(6), 283-289. https://doi.org/10.11648/j.si.20160406.17

    Copy | Download

    ACS Style

    Gao Xiaoqiang; Li Pan; Zheng Zhong; Jiang Shenglong; You Xiao. Studying on a Genetic-Simulation Optimization Algorithm Method for Steel Crane Scheduling Problem. Sci. Innov. 2016, 4(6), 283-289. doi: 10.11648/j.si.20160406.17

    Copy | Download

    AMA Style

    Gao Xiaoqiang, Li Pan, Zheng Zhong, Jiang Shenglong, You Xiao. Studying on a Genetic-Simulation Optimization Algorithm Method for Steel Crane Scheduling Problem. Sci Innov. 2016;4(6):283-289. doi: 10.11648/j.si.20160406.17

    Copy | Download

  • @article{10.11648/j.si.20160406.17,
      author = {Gao Xiaoqiang and Li Pan and Zheng Zhong and Jiang Shenglong and You Xiao},
      title = {Studying on a Genetic-Simulation Optimization Algorithm Method for Steel Crane Scheduling Problem},
      journal = {Science Innovation},
      volume = {4},
      number = {6},
      pages = {283-289},
      doi = {10.11648/j.si.20160406.17},
      url = {https://doi.org/10.11648/j.si.20160406.17},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20160406.17},
      abstract = {For solving crane scheduling problem in steelmaking-continuous casting process, a hybrid method of integrating genetic algorithm and simulation was formulated to minimize the operation time of tasks by considering full ladles, empty ladles and auxiliary tasks as transportation tasks. The crane selected sequence was designed as chromosome coding. The initial population was generated by employing the crane selection rules in the simulation model, and then evolved optimized by using the genetic operations such as selection, crossover and mutation. The chromosome is evaluated through generating a feasible crane schedule by employing the attribute updating rules and collision eliminating rules in the simulation model. The new crane scheduling could be generated through simulation model based on the new species. Therefore, more excellent individuals will be produced along with the evolutionary process. Thus a better crane scheduling scheme could be obtained finally. In the process of initialization, the high quality initial population was generated in the simulation model. In the iterative process, simulation model also could generate the feasible crane scheduling schemes based on the given cranes selection sequence. To validate this model, experiments were conducted by using the production data in the casting span of a steel plant. The results demonstrate the feasibility and efficiency of this method, which provides a useful tool for crane scheduling in actual production.},
     year = {2016}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Studying on a Genetic-Simulation Optimization Algorithm Method for Steel Crane Scheduling Problem
    AU  - Gao Xiaoqiang
    AU  - Li Pan
    AU  - Zheng Zhong
    AU  - Jiang Shenglong
    AU  - You Xiao
    Y1  - 2016/12/07
    PY  - 2016
    N1  - https://doi.org/10.11648/j.si.20160406.17
    DO  - 10.11648/j.si.20160406.17
    T2  - Science Innovation
    JF  - Science Innovation
    JO  - Science Innovation
    SP  - 283
    EP  - 289
    PB  - Science Publishing Group
    SN  - 2328-787X
    UR  - https://doi.org/10.11648/j.si.20160406.17
    AB  - For solving crane scheduling problem in steelmaking-continuous casting process, a hybrid method of integrating genetic algorithm and simulation was formulated to minimize the operation time of tasks by considering full ladles, empty ladles and auxiliary tasks as transportation tasks. The crane selected sequence was designed as chromosome coding. The initial population was generated by employing the crane selection rules in the simulation model, and then evolved optimized by using the genetic operations such as selection, crossover and mutation. The chromosome is evaluated through generating a feasible crane schedule by employing the attribute updating rules and collision eliminating rules in the simulation model. The new crane scheduling could be generated through simulation model based on the new species. Therefore, more excellent individuals will be produced along with the evolutionary process. Thus a better crane scheduling scheme could be obtained finally. In the process of initialization, the high quality initial population was generated in the simulation model. In the iterative process, simulation model also could generate the feasible crane scheduling schemes based on the given cranes selection sequence. To validate this model, experiments were conducted by using the production data in the casting span of a steel plant. The results demonstrate the feasibility and efficiency of this method, which provides a useful tool for crane scheduling in actual production.
    VL  - 4
    IS  - 6
    ER  - 

    Copy | Download

Author Information
  • College of Economics and Business Administration, Chongqing University, Chongqing, China

  • College of Economics and Business Administration, Chongqing University, Chongqing, China

  • College of Material Science and Engineering, Chongqing University, Chongqing, China

  • College of Material Science and Engineering, Chongqing University, Chongqing, China

  • College of Material Science and Engineering, Chongqing University, Chongqing, China

  • Sections