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Modeling and Multiobjective Optimization for Energy-Aware Hybrid Flow Shop Scheduling

In: Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2013)

Author

Listed:
  • Ji-hong Yan

    (Harbin Institute of Technology)

  • Fen-yang Zhang

    (Harbin Institute of Technology)

  • Xin Li

    (Harbin Institute of Technology)

  • Zi-mo Wang

    (Harbin Institute of Technology)

  • Wei Wang

    (Harbin Institute of Technology)

Abstract

In this paper, a multiobjective scheduling problem for energy-aware Hybrid Flow Shop (HFS) is studied, in which minimal makespan and energy consumption are set as the objectives. The energy consumption model of HFS is established, in which the energy consumption is categorized into five parts as Processing Energy (PE), Adjusting Energy (AE), Transport Energy (TE), Waiting Energy (WE) and Routine Energy (RE). Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm (NSGA-2) are applied to obtain optimal schedules. Simulation results demonstrate that the proposed method is effective in supporting energy efficiency management in HSF.

Suggested Citation

  • Ji-hong Yan & Fen-yang Zhang & Xin Li & Zi-mo Wang & Wei Wang, 2014. "Modeling and Multiobjective Optimization for Energy-Aware Hybrid Flow Shop Scheduling," Springer Books, in: Ershi Qi & Jiang Shen & Runliang Dou (ed.), Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2013), edition 127, pages 741-751, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-40060-5_71
    DOI: 10.1007/978-3-642-40060-5_71
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