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Research on permutation flow shop scheduling problems with general position-dependent learning effects

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  • Lin-Hui Sun
  • Kai Cui
  • Ju-Hong Chen
  • Jun Wang
  • Xian-Chen He

Abstract

Machine learning exists in many realistic scheduling situations. This study focuses on permutation flow shop scheduling problems, where the actual processing time of a job is defined by a general non-increasing function of its scheduled position, i.e., general position-dependent learning effects. The objective functions are to minimize the total completion time, the makespan, the total weighted completion time, and the total weighted discounted completion time, respectively. To solve these problems, we present approximation algorithms based on the optimal permutations for the corresponding single machine scheduling problems and analyze their worst-case error bound. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:211:y:2013:i:1:p:473-480:10.1007/s10479-013-1481-6
    DOI: 10.1007/s10479-013-1481-6
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    References listed on IDEAS

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    1. Xingong Zhang & Guangle Yan & Wanzhen Huang & Guochun Tang, 2011. "Single-machine scheduling problems with time and position dependent processing times," Annals of Operations Research, Springer, vol. 186(1), pages 345-356, June.
    2. 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.
    3. Fehmi Tanrisever & Erhan Kutanoglu, 2008. "Forming and scheduling jobs with capacitated containers in semiconductor manufacturing: Single machine problem," Annals of Operations Research, Springer, vol. 159(1), pages 5-24, March.
    4. Evgeny Shchepin & Nodari Vakhania, 2008. "On the geometry, preemptions and complexity of multiprocessor and shop scheduling," Annals of Operations Research, Springer, vol. 159(1), pages 183-213, March.
    5. Evgeny Gafarov & Alexander Lazarev & Frank Werner, 2013. "Single machine total tardiness maximization problems: complexity and algorithms," Annals of Operations Research, Springer, vol. 207(1), pages 121-136, August.
    6. Kjetil Fagerholt & Lars Hvattum & Trond Johnsen & Jarl Korsvik, 2013. "Routing and scheduling in project shipping," Annals of Operations Research, Springer, vol. 207(1), pages 67-81, August.
    7. Kailiang Xu & Zuren Feng & Liangjun Ke, 2011. "Single machine scheduling with total tardiness criterion and convex controllable processing times," Annals of Operations Research, Springer, vol. 186(1), pages 383-391, June.
    8. 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.
    9. Hoksung Yau & Leyuan Shi, 2009. "Nested partitions for the large-scale extended job shop scheduling problem," Annals of Operations Research, Springer, vol. 168(1), pages 23-39, April.
    10. Ji-Bo Wang & Ming-Zheng Wang, 2011. "Worst-case behavior of simple sequencing rules in flow shop scheduling with general position-dependent learning effects," Annals of Operations Research, Springer, vol. 191(1), pages 155-169, November.
    11. Smutnicki, Czeslaw, 1998. "Some results of the worst-case analysis for flow shop scheduling," European Journal of Operational Research, Elsevier, vol. 109(1), pages 66-87, August.
    12. Biskup, Dirk, 2008. "A state-of-the-art review on scheduling with learning effects," European Journal of Operational Research, Elsevier, vol. 188(2), pages 315-329, July.
    13. Chin-Chia Wu & Yunqiang Yin & Wen-Hsiang Wu & Shuenn-Ren Cheng, 2012. "Some polynomial solvable single-machine scheduling problems with a truncation sum-of-processing-times-based learning effect," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 6(4), pages 441-453.
    14. Wu, Chin-Chia & Lee, Wen-Chiung, 2009. "A note on the total completion time problem in a permutation flowshop with a learning effect," European Journal of Operational Research, Elsevier, vol. 192(1), pages 343-347, January.
    15. Liji Shen & Lars Mönch & Udo Buscher, 2013. "An iterative approach for the serial batching problem with parallel machines and job families," Annals of Operations Research, Springer, vol. 206(1), pages 425-448, July.
    16. Lin-Hui Sun & Kai Cui & Ju-Hong Chen & Jun Wang & Xian-Chen He, 2013. "Some results of the worst-case analysis for flow shop scheduling with a learning effect," Annals of Operations Research, Springer, vol. 211(1), pages 481-490, December.
    17. J-B Wang & M-Z Wang, 2012. "Worst-case analysis for flow shop scheduling problems with an exponential learning effect," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(1), pages 130-137, January.
    18. Xu, Zhiyong & Sun, Linyan & Gong, Juntao, 2008. "Worst-case analysis for flow shop scheduling with a learning effect," International Journal of Production Economics, Elsevier, vol. 113(2), pages 748-753, June.
    19. Carlos Mencía & María Sierra & Ramiro Varela, 2013. "Depth-first heuristic search for the job shop scheduling problem," Annals of Operations Research, Springer, vol. 206(1), pages 265-296, July.
    20. Adam Janiak & Mikhail Kovalyov & Maciej Lichtenstein, 2013. "Strong NP-hardness of scheduling problems with learning or aging effect," Annals of Operations Research, Springer, vol. 206(1), pages 577-583, July.
    21. Kangbok Lee & Joseph Leung & Michael Pinedo, 2013. "Makespan minimization in online scheduling with machine eligibility," Annals of Operations Research, Springer, vol. 204(1), pages 189-222, April.
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    Cited by:

    1. 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.
    2. 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.
    3. Bai, Danyu & Tang, Mengqian & Zhang, Zhi-Hai & Santibanez-Gonzalez, Ernesto DR, 2018. "Flow shop learning effect scheduling problem with release dates," Omega, Elsevier, vol. 78(C), pages 21-38.
    4. 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.
    5. 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.

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