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Energy-oriented bi-objective optimization for the tempered glass scheduling

Author

Listed:
  • Liu, Ming
  • Yang, Xuenan
  • Chu, Feng
  • Zhang, Jiantong
  • Chu, Chengbin

Abstract

This paper investigates a real life bi-objective hybrid flow shop scheduling problem in an energy-intensive manufacturing system, in which glass is produced successively in cutting, printing and tempering stages. The problem aims to simultaneously optimize makespan and the total electricity cost under a time-of-use electricity pricing policy. The glass production has to respect the following environments: (i) the cutting and printing operations are processed in parallel machine environments; (ii) the tempering operation is processed on a batch machine; (iii) machine eligibility and setup time have to be considered in the cutting and printing stages; (iv) the whole manufacturing system is under a time-of-use electricity pricing policy. For the problem, an integer programming model is firstly proposed and shown to be strongly NP-hard. Then a model-based heuristic is adopted and a bi-objective differential evolution algorithm (BODE) is devised based on problem features. Computational experiments on randomly generated instances demonstrated that the BODE outperforms the model-based heuristic in terms of computation time and solution quality. Moreover, with mild increase on computation burden, the BODE significantly outperforms the classic NSGA II in terms of solution quality.

Suggested Citation

  • Liu, Ming & Yang, Xuenan & Chu, Feng & Zhang, Jiantong & Chu, Chengbin, 2020. "Energy-oriented bi-objective optimization for the tempered glass scheduling," Omega, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:jomega:v:90:y:2020:i:c:s0305048317312665
    DOI: 10.1016/j.omega.2018.11.004
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    References listed on IDEAS

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    Cited by:

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    4. Neufeld, Janis S. & Schulz, Sven & Buscher, Udo, 2023. "A systematic review of multi-objective hybrid flow shop scheduling," European Journal of Operational Research, Elsevier, vol. 309(1), pages 1-23.

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