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Minmax common flow-allowance problems with convex resource allocation and position-dependent workloads

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  • Baruch Mor

    (Ariel University)

Abstract

We study minmax due-date based on common flow-allowance assignment and scheduling problems on a single machine, and extend known results in scheduling theory by considering convex resource allocation. The total cost function of a given job consists of its earliness, tardiness and flow-allowance cost components. Thus, the common flow-allowance and the actual jobs’ processing times are decision variables, implying that the due-dates and actual processing times can be controlled by allocating additional resource to the job operations. Consequently, our goal is to optimize a cost function by seeking the optimal job sequence, the optimal job-dependent due-dates along with the actual processing times. In all addressed problems we aim to minimize the maximal cost among all the jobs subject to a constraint on the resource consumption. We start by analyzing and solving the problem with position-independent workloads and then proceed to position-dependent workloads. Finally, the results are generalized to the method of common due-window. For all studied problems closed form solutions are provided, leading to polynomial time solutions.

Suggested Citation

  • Baruch Mor, 2022. "Minmax common flow-allowance problems with convex resource allocation and position-dependent workloads," Journal of Combinatorial Optimization, Springer, vol. 43(1), pages 79-97, January.
    • Handle: RePEc:spr:jcomop:v:43:y:2022:i:1:d:10.1007_s10878-021-00746-w
    DOI: 10.1007/s10878-021-00746-w
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    References listed on IDEAS

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    1. Li, Gang & Wang, Xiao-Yuan & Wang, Ji-Bo & Sun, Lin-Yan, 2013. "Worst case analysis of flow shop scheduling problems with a time-dependent learning effect," International Journal of Production Economics, Elsevier, vol. 142(1), pages 98-104.
    2. Jun Pei & Bayi Cheng & Xinbao Liu & Panos M. Pardalos & Min Kong, 2019. "Single-machine and parallel-machine serial-batching scheduling problems with position-based learning effect and linear setup time," Annals of Operations Research, Springer, vol. 272(1), pages 217-241, January.
    3. Baruch Mor & Gur Mosheiov, 2017. "A two-agent single machine scheduling problem with due-window assignment and a common flow-allowance," Journal of Combinatorial Optimization, Springer, vol. 33(4), pages 1454-1468, May.
    4. Oron, Daniel, 2016. "Scheduling controllable processing time jobs with position-dependent workloads," International Journal of Production Economics, Elsevier, vol. 173(C), pages 153-160.
    5. Baruch Mor & Gur Mosheiov & Dana Shapira, 2020. "Flowshop scheduling with learning effect and job rejection," Journal of Scheduling, Springer, vol. 23(6), pages 631-641, December.
    6. Dujuan Wang & Yunqiang Yin & T.C.E. Cheng, 2017. "A bicriterion approach to common flow allowances due window assignment and scheduling with controllable processing times," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(1), pages 41-63, February.
    7. Wei-Wei Liu & Chong Jiang, 2020. "Flow Shop Resource Allocation Scheduling with Due Date Assignment, Learning Effect and Position-Dependent Weights," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 37(03), pages 1-27, April.
    8. S. S. Panwalkar & M. L. Smith & A. Seidmann, 1982. "Common Due Date Assignment to Minimize Total Penalty for the One Machine Scheduling Problem," Operations Research, INFORMS, vol. 30(2), pages 391-399, April.
    9. Lu Liu & Jian-Jun Wang & Xiao-Yuan Wang, 2016. "Single machine due-window assignment scheduling with resource-dependent processing times to minimise total resource consumption cost," International Journal of Production Research, Taylor & Francis Journals, vol. 54(4), pages 1186-1195, February.
    10. Xiaoyun Xiong & Dujuan Wang & T.C. Edwin Cheng & Chin-Chia Wu & Yunqiang Yin, 2018. "Single-machine scheduling and common due date assignment with potential machine disruption," International Journal of Production Research, Taylor & Francis Journals, vol. 56(3), pages 1345-1360, February.
    11. Yunqiang Yin & Du‐Juan Wang & Chin‐Chia Wu & T.C.E. Cheng, 2016. "CON/SLK due date assignment and scheduling on a single machine with two agents," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(5), pages 416-429, August.
    12. Du-Juan Wang & Yunqiang Yin & Shuenn-Ren Cheng & T.C.E. Cheng & Chin-Chia Wu, 2016. "Due date assignment and scheduling on a single machine with two competing agents," International Journal of Production Research, Taylor & Francis Journals, vol. 54(4), pages 1152-1169, February.
    13. Min Ji & Wenya Zhang & Lijuan Liao & T. C. E. Cheng & Yuanyuan Tan, 2019. "Multitasking parallel-machine scheduling with machine-dependent slack due-window assignment," International Journal of Production Research, Taylor & Francis Journals, vol. 57(6), pages 1667-1684, March.
    14. Radosław Rudek, 2012. "Scheduling problems with position dependent job processing times: computational complexity results," Annals of Operations Research, Springer, vol. 196(1), pages 491-516, July.
    15. Lin-Hui Sun & Kai Cui & Ju-Hong Chen & Jun Wang & Xian-Chen He, 2013. "Research on permutation flow shop scheduling problems with general position-dependent learning effects," Annals of Operations Research, Springer, vol. 211(1), pages 473-480, December.
    16. Baruch Mor & Gur Mosheiov, 2018. "A note: minimizing total absolute deviation of job completion times on unrelated machines with general position-dependent processing times and job-rejection," Annals of Operations Research, Springer, vol. 271(2), pages 1079-1085, December.
    17. Xinyu Sun & Xin-Na Geng & Ji-Bo Wang & Feng Liu, 2019. "Convex resource allocation scheduling in the no-wait flowshop with common flow allowance and learning effect," International Journal of Production Research, Taylor & Francis Journals, vol. 57(6), pages 1873-1891, March.
    18. Mor, Baruch & Mosheiov, Gur, 2016. "Minsum and minmax scheduling on a proportionate flowshop with common flow-allowance," European Journal of Operational Research, Elsevier, vol. 254(2), pages 360-370.
    19. Daniel Oron, 2016. "Scheduling controllable processing time jobs in a deteriorating environment," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(3), pages 535-535, March.
    20. Fu Gao & Mengqi Liu & Jian-Jun Wang & Yuan-Yuan Lu, 2018. "No-wait two-machine permutation flow shop scheduling problem with learning effect, common due date and controllable job processing times," International Journal of Production Research, Taylor & Francis Journals, vol. 56(6), pages 2361-2369, March.
    21. 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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