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A hybrid multi-objective evolutionary algorithm based on NSGA-II for practical scheduling with release times in steel plants

Author

Listed:
  • Jianyu Long

    (Chongqing University
    University of Florida)

  • Zhong Zheng

    (Chongqing University)

  • Xiaoqiang Gao

    (Chongqing University)

  • Panos M Pardalos

    (University of Florida)

Abstract

The hot metal is produced from the blast furnaces in the iron plant and should be processed as soon as possible in the subsequent steel plant for energy saving. Therefore, the release times of hot metal have an influence on the scheduling of a steel plant. In this paper, the scheduling problem with release times for steel plants is studied. The production objectives and constraints related to the release times are clarified, and a new multi-objective scheduling model is built. For the solving of the multi-objective optimization, a hybrid multi-objective evolutionary algorithm based on non-dominated sorting genetic algorithm-II (NSGA-II) is proposed. In the hybrid multi-objective algorithm, an efficient decoding heuristic (DH) and a non-dominated solution construction method (NSCM) are proposed based on the problem-specific characteristics. During the evolutionary process, individuals with different solutions may have a same chromosome because the NSCM constructs non-dominated solutions just based on the solution found by DH. Therefore, three operations in the original NSGA-II process are modified to avoid identical chromosomes in the evolutionary operations. Computational tests show that the proposed hybrid algorithm based on NSGA-II is feasible and effective for the multi-objective scheduling with release times.

Suggested Citation

  • Jianyu Long & Zhong Zheng & Xiaoqiang Gao & Panos M Pardalos, 2016. "A hybrid multi-objective evolutionary algorithm based on NSGA-II for practical scheduling with release times in steel plants," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(9), pages 1184-1199, September.
    • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:9:d:10.1057_jors.2016.17
    DOI: 10.1057/jors.2016.17
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    References listed on IDEAS

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    1. Ruiz, Rubén & Vázquez-Rodríguez, José Antonio, 2010. "The hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 1-18, August.
    2. Tang, Lixin & Liu, Jiyin & Rong, Aiying & Yang, Zihou, 2001. "A review of planning and scheduling systems and methods for integrated steel production," European Journal of Operational Research, Elsevier, vol. 133(1), pages 1-20, August.
    3. Mao, Kun & Pan, Quan-ke & Pang, Xinfu & Chai, Tianyou, 2014. "A novel Lagrangian relaxation approach for a hybrid flowshop scheduling problem in the steelmaking-continuous casting process," European Journal of Operational Research, Elsevier, vol. 236(1), pages 51-60.
    4. Tang, Lixin & Liu, Jiyin & Rong, Aiying & Yang, Zihou, 2000. "A mathematical programming model for scheduling steelmaking-continuous casting production," European Journal of Operational Research, Elsevier, vol. 120(2), pages 423-435, January.
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    2. Yaping Fu & Hongfeng Wang & Guangdong Tian & Zhiwu Li & Hesuan Hu, 2019. "Two-agent stochastic flow shop deteriorating scheduling via a hybrid multi-objective evolutionary algorithm," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2257-2272, June.

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