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Research on scheduling with job-dependent learning effect and convex resource-dependent processing times

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  • Ji-Bo Wang
  • Jian-Jun Wang

Abstract

We study resource allocation scheduling with job-dependent learning effect on a single machine with or without due date assignment considerations. For a convex resource processing time function, we provide a polynomial time algorithm to find the optimal job sequence, and resource allocations that minimise the schedule criterion (the total compression cost) subject to the constraint that the total compression cost (the schedule criterion) is less than or equal to a fixed amount.

Suggested Citation

  • Ji-Bo Wang & Jian-Jun Wang, 2015. "Research on scheduling with job-dependent learning effect and convex resource-dependent processing times," International Journal of Production Research, Taylor & Francis Journals, vol. 53(19), pages 5826-5836, October.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:19:p:5826-5836
    DOI: 10.1080/00207543.2015.1010746
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    Citations

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    Cited by:

    1. Wu, Yu-Bin & Wan, Long & Wang, Xiao-Yuan, 2015. "Study on due-window assignment scheduling based on common flow allowance," International Journal of Production Economics, Elsevier, vol. 165(C), pages 155-157.
    2. Xiong, Jian & Leus, Roel & Yang, Zhenyu & Abbass, Hussein A., 2016. "Evolutionary multi-objective resource allocation and scheduling in the Chinese navigation satellite system project," European Journal of Operational Research, Elsevier, vol. 251(2), pages 662-675.
    3. Du-Juan Wang & Yunqiang Yin & Mengqi Liu, 2016. "Bicriteria scheduling problems involving job rejection, controllable processing times and rate-modifying activity," International Journal of Production Research, Taylor & Francis Journals, vol. 54(12), pages 3691-3705, June.
    4. Norelhouda Sekkal & Fayçal Belkaid, 2020. "A multi-objective simulated annealing to solve an identical parallel machine scheduling problem with deterioration effect and resources consumption constraints," Journal of Combinatorial Optimization, Springer, vol. 40(3), pages 660-696, October.
    5. Norelhouda Sekkal & Fayçal Belkaid, 0. "A multi-objective simulated annealing to solve an identical parallel machine scheduling problem with deterioration effect and resources consumption constraints," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-37.
    6. Heuser, Patricia & Tauer, Björn, 2023. "Single-machine scheduling with product category-based learning and forgetting effects," Omega, Elsevier, vol. 115(C).
    7. Hongyu He & Mengqi Liu & Ji-Bo Wang, 2017. "Resource constrained scheduling with general truncated job-dependent learning effect," Journal of Combinatorial Optimization, Springer, vol. 33(2), pages 626-644, February.
    8. Xuyin Wang & Xiangpei Hu & Weiguo Liu, 2015. "Scheduling with Deteriorating Jobs and Non-Simultaneous Machine Available Times," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 32(06), pages 1-13, December.
    9. Zhenyou Wang & Cai-Min Wei & Yuan-Yuan Lu, 2016. "Permutation Flow Shop Problem with Shortening Job Processing Times," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(04), pages 1-14, August.
    10. Zhusong Liu & Zhenyou Wang & Yuan-Yuan Lu, 2017. "A Bicriteria Approach for Single Machine Scheduling with Resource Allocation, Learning Effect and a Deteriorating Maintenance Activity," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(04), pages 1-16, August.
    11. Zhenyou Wang & Cai-Min Wei & Yu-Bin Wu, 2016. "Single Machine Two-Agent Scheduling with Deteriorating Jobs," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(05), pages 1-17, October.
    12. Lin-Hui Sun & Kai Cui & Ju-hong Chen & Jun Wang, 2016. "Due date assignment and convex resource allocation scheduling with variable job processing times," International Journal of Production Research, Taylor & Francis Journals, vol. 54(12), pages 3551-3560, June.

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