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Less is more approach for competing groups scheduling with different learning effects

Author

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  • Baoyu Liao

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

  • Xingming Wang

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

  • Xing Zhu

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

  • Shanlin Yang

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

  • Panos M. Pardalos

    (University of Florida)

Abstract

This paper investigates a two-competing group scheduling problem on serial-batching machines considering setup times and truncated job-dependent learning effects. The objective is to minimize the makespan of one group with truncated learning effect under the constraint that the makespan of the other group with general learning effect cannot exceed an upper bound. We propose some structural properties for the scheduling problem on a given machine, and design a Less-is-more-based iterative reference greedy algorithm for parallel machines scheduling problems. The computational results show that the proposed algorithm can solve the studied problems effectively.

Suggested Citation

  • Baoyu Liao & Xingming Wang & Xing Zhu & Shanlin Yang & Panos M. Pardalos, 2020. "Less is more approach for competing groups scheduling with different learning effects," Journal of Combinatorial Optimization, Springer, vol. 39(1), pages 33-54, January.
  • Handle: RePEc:spr:jcomop:v:39:y:2020:i:1:d:10.1007_s10878-019-00452-8
    DOI: 10.1007/s10878-019-00452-8
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    References listed on IDEAS

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    7. Wenjuan Fan & Jun Pei & Xinbao Liu & Panos M. Pardalos & Min Kong, 2018. "Serial-batching group scheduling with release times and the combined effects of deterioration and truncated job-dependent learning," Journal of Global Optimization, Springer, vol. 71(1), pages 147-163, May.
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    Cited by:

    1. Jia-Xuan Yan & Na Ren & Hong-Bin Bei & Han Bao & Ji-Bo Wang, 2022. "Scheduling with Resource Allocation, Deteriorating Effect and Group Technology to Minimize Total Completion Time," Mathematics, MDPI, vol. 10(16), pages 1-15, August.

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