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Research on Group Scheduling With Effects of Learning and Resource Allocations

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  • Tianyi Zhao

Abstract

This paper addresses the single‐machine group scheduling with effects of learning and resource allocations. By effects of learning and resource allocations, we mean that the group setup times and job processing times are functions of their resource allocations and positions. For the convex resource allocation, we give a bicriteria analysis where the first cost is the makespan, and the second cost is the total resource consumption (i.e., resource utilization). We show that three versions of both of these costs are polynomially solvable.

Suggested Citation

  • Tianyi Zhao, 2025. "Research on Group Scheduling With Effects of Learning and Resource Allocations," Journal of Mathematics, John Wiley & Sons, vol. 2025(1).
    • Handle: RePEc:wly:jjmath:v:2025:y:2025:i:1:n:4146871
    DOI: 10.1155/jom/4146871
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    References listed on IDEAS

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    1. Xinyu Sun & Xin-Na Geng & Tao Liu, 2020. "Due-window assignment scheduling in the proportionate flow shop setting," Annals of Operations Research, Springer, vol. 292(1), pages 113-131, September.
    2. Zheng Liu & Ji-Bo Wang, 2024. "Single-Machine Scheduling with Simultaneous Learning Effects and Delivery Times," Mathematics, MDPI, vol. 12(16), pages 1-20, August.
    3. Dan-Yang Lv & Ji-Bo Wang, 2025. "Single-machine group technology scheduling with resource allocation and slack due window assignment including minmax criterion," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 76(8), pages 1696-1712, August.
    4. Bing Bai & Cai-Min Wei & Hong-Yu He & Ji-Bo Wang, 2024. "Study on Single-Machine Common/Slack Due-Window Assignment Scheduling with Delivery Times, Variable Processing Times and Outsourcing," Mathematics, MDPI, vol. 12(18), pages 1-19, September.
    5. Xinyu Sun & Xin-Na Geng & Feng Liu, 2021. "Flow shop scheduling with general position weighted learning effects to minimise total weighted completion time," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(12), pages 2674-2689, December.
    6. Jin Qian & Yu Zhan, 2021. "The Due Date Assignment Scheduling Problem with Delivery Times and Truncated Sum-of-Processing-Times-Based Learning Effect," Mathematics, MDPI, vol. 9(23), pages 1-14, November.
    7. Shi-Sheng Li & Ren-Xia Chen, 2023. "Competitive two-agent scheduling with release dates and preemption on a single machine," Journal of Scheduling, Springer, vol. 26(3), pages 227-249, June.
    8. Dvir Shabtay & Daniel Oron, 2016. "Proportionate flow-shop scheduling with rejection," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(5), pages 752-769, May.
    9. Dingyu Wang & Chunming Ye & Antonio Di Crescenzo, 2021. "Group Scheduling with Learning Effect and Random Processing Time," Journal of Mathematics, Hindawi, vol. 2021, pages 1-6, July.
    10. Jun Pei & Xingming Wang & Wenjuan Fan & Panos M. Pardalos & Xinbao Liu, 2019. "Scheduling step-deteriorating jobs on bounded parallel-batching machines to maximise the total net revenue," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1830-1847, October.
    11. Bihui Cheng & Wencheng Wang & Ji Gao, 2023. "A Combinatorial Approximation Algorithm for the Vector Scheduling with Submodular Penalties on Parallel Machines," Journal of Mathematics, Hindawi, vol. 2023, pages 1-8, November.
    12. Xinyu Sun & Tao Liu & Xin-Na Geng & Yang Hu & Jing-Xiao Xu, 2023. "Optimization of scheduling problems with deterioration effects and an optional maintenance activity," Journal of Scheduling, Springer, vol. 26(3), pages 251-266, June.
    13. Taillard, E., 1993. "Benchmarks for basic scheduling problems," European Journal of Operational Research, Elsevier, vol. 64(2), pages 278-285, January.
    14. Miao Li & Dries Goossens, 2025. "Grouping and scheduling multiple sports leagues: an integrated approach," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 76(4), pages 739-757, April.
    15. Yurong Zhang & Xinyu Sun & Tao Liu & Jiayin Wang & Xin-Na Geng, 2025. "Single-machine scheduling simultaneous consideration of resource allocations and exponential time-dependent learning effects," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 76(3), pages 528-540, March.
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