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

Gao Xiaoqiang; Li Pan; Zheng Zhong; Jiang Shenglong; You Xiao

doi:doi:10.11648/j.si.20160406.17

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

Gao Xiaoqiang, Li Pan, Zheng Zhong, Jiang Shenglong, You Xiao

Published in Science Innovation (Volume 4, Issue 6)

Received: 6 December 2016 Accepted: Published: 7 December 2016

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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), 2024. Published by Science Publishing Group

Keywords

Crane Scheduling, Simulation Model, Genetic Algorithm, Simulation Rules

References

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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

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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

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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

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@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}
}

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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 -

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Author Information

Gao Xiaoqiang

College of Economics and Business Administration, Chongqing University, Chongqing, China
Li Pan

College of Economics and Business Administration, Chongqing University, Chongqing, China
Zheng Zhong

College of Material Science and Engineering, Chongqing University, Chongqing, China
Jiang Shenglong

College of Material Science and Engineering, Chongqing University, Chongqing, China
You Xiao

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

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Plain Text BibTeX RIS

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

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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

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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

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@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}
}

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