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Decoding methods for the flow shop scheduling with peak power consumption constraints

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  • Jing-jing Wang
  • Ling Wang

Abstract

The permutation flow shop scheduling problem (PFSP) is of wide application backgrounds and plays an important role in the manufacturing systems. With the serious energy concerns in manufacturing enterprises, peak power consumption is considered one of the significant issues. For the PFSP with peak power consumption constraints (PFSPP), the real-time power consumption cannot exceed a given peak power at any time. Since the classical first-come first-serve scheduling method is not suitable for the PFSPP, this paper addresses the decoding methods to obtain feasible schedules based on the permutation encoding scheme. First, an earliest processing rule (EPR) is designed to determine the starting time of each operation, satisfying the power consumption constraints. Then, five decoding methods based on EPR are proposed to determine the suitable priority between the operations to yield feasible schedules with high quality. After analysing the complexity of the proposed decoding methods and comparing the performances via extensive numerical tests, some suggestions are provided for solving the PFSPP with different scales and power constraints.

Suggested Citation

  • Jing-jing Wang & Ling Wang, 2019. "Decoding methods for the flow shop scheduling with peak power consumption constraints," International Journal of Production Research, Taylor & Francis Journals, vol. 57(10), pages 3200-3218, May.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:10:p:3200-3218
    DOI: 10.1080/00207543.2019.1571252
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    Cited by:

    1. Weiwei Cui & Biao Lu, 2020. "A Bi-Objective Approach to Minimize Makespan and Energy Consumption in Flow Shops with Peak Demand Constraint," Sustainability, MDPI, vol. 12(10), pages 1-22, May.

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