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Scheduling problem in seru production system considering DeJong’s learning effect and job splitting

Author

Listed:
  • Zhe Zhang

    (Nanjing University of Science and Technology)

  • Xiaoling Song

    (Nanjing University of Science and Technology)

  • Huijun Huang

    (Nanjing University of Science and Technology)

  • Yong Yin

    (Doshisha University)

  • Benjamin Lev

    (Drexel University)

Abstract

Seru is a relatively new type of Japanese production mode originated from the electronic assembly industry. In practice, seru production has been proven to be efficient, flexible, response quickly, and can cope with the fluctuating production demands in a current volatile market. This paper focuses on scheduling problems in seru production system. Motivated by the realty of labor-intensive assembly industry, we consider learning effect of workers and job splitting with the objective of minimizing the total completion time. A nonlinear integer programming model for the seru scheduling problem is provided, and it is proved to be polynomial solvable. Therefore, a branch and bound algorithm is designed for small sized seru scheduling problems, while a local search-based hybrid genetic algorithm employing shortest processing time rule is provided for large sized problems. Finally, computational experiments are conducted, and the results demonstrate the practicability of the proposed seru scheduling model and the efficiency of our solution methods.

Suggested Citation

  • Zhe Zhang & Xiaoling Song & Huijun Huang & Yong Yin & Benjamin Lev, 2022. "Scheduling problem in seru production system considering DeJong’s learning effect and job splitting," Annals of Operations Research, Springer, vol. 312(2), pages 1119-1141, May.
    • Handle: RePEc:spr:annopr:v:312:y:2022:i:2:d:10.1007_s10479-021-04515-0
    DOI: 10.1007/s10479-021-04515-0
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    References listed on IDEAS

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    1. Zhang, Zhe & Song, Xiaoling & Huang, Huijung & Zhou, Xiaoyang & Yin, Yong, 2022. "Logic-based Benders decomposition method for the seru scheduling problem with sequence-dependent setup time and DeJong’s learning effect," European Journal of Operational Research, Elsevier, vol. 297(3), pages 866-877.
    2. Aleda Roth & Jaya Singhal & Kalyan Singhal & Christopher S. Tang, 2016. "Knowledge Creation and Dissemination in Operations and Supply Chain Management," Production and Operations Management, Production and Operations Management Society, vol. 25(9), pages 1473-1488, September.
    3. Tzu-Li Chen & Chen-Yang Cheng & Yi-Han Chou, 2020. "Multi-objective genetic algorithm for energy-efficient hybrid flow shop scheduling with lot streaming," Annals of Operations Research, Springer, vol. 290(1), pages 813-836, July.
    4. Zhang, XiaoLi & Liu, ChenGuang & Li, WenJuan & Evans, Steve & Yin, Yong, 2017. "Effects of key enabling technologies for seru production on sustainable performance," Omega, Elsevier, vol. 66(PB), pages 290-307.
    5. Lan Luo & Zhe Zhang & Yong Yin, 2017. "Modelling and numerical analysis of seru loading problem under uncertainty," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 11(2), pages 185-204.
    6. 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.
    7. Wei Sun & Yang Yu & Qi Lou & Junwei Wang & Yuechao Guan, 2020. "Reducing the total tardiness by Seru production: model, exact and cooperative coevolution solutions," International Journal of Production Research, Taylor & Francis Journals, vol. 58(21), pages 6441-6452, November.
    8. Biskup, Dirk, 1999. "Single-machine scheduling with learning considerations," European Journal of Operational Research, Elsevier, vol. 115(1), pages 173-178, May.
    9. Rabia Nessah & Chengbin Chu, 2010. "Infinite split scheduling: a new lower bound of total weighted completion time on parallel machines with job release dates and unavailability periods," Annals of Operations Research, Springer, vol. 181(1), pages 359-375, December.
    10. Yong Yin & Kathryn E. Stecke & Dongni Li, 2018. "The evolution of production systems from Industry 2.0 through Industry 4.0," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 848-861, January.
    11. Mosheiov, Gur, 2001. "Scheduling problems with a learning effect," European Journal of Operational Research, Elsevier, vol. 132(3), pages 687-693, August.
    12. A Bachman & A Janiak, 2004. "Scheduling jobs with position-dependent processing times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(3), pages 257-264, March.
    13. Li, Xinyu & Gao, Liang, 2016. "An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem," International Journal of Production Economics, Elsevier, vol. 174(C), pages 93-110.
    14. Yu, Yang & Tang, Jiafu & Gong, Jun & Yin, Yong & Kaku, Ikou, 2014. "Mathematical analysis and solutions for multi-objective line-cell conversion problem," European Journal of Operational Research, Elsevier, vol. 236(2), pages 774-786.
    15. Mosheiov, Gur & Sidney, Jeffrey B., 2003. "Scheduling with general job-dependent learning curves," European Journal of Operational Research, Elsevier, vol. 147(3), pages 665-670, June.
    16. Hyun-Jung Kim, 2018. "Bounds for parallel machine scheduling with predefined parts of jobs and setup time," Annals of Operations Research, Springer, vol. 261(1), pages 401-412, February.
    17. Huang, Rong-Hwa, 2010. "Multi-objective job-shop scheduling with lot-splitting production," International Journal of Production Economics, Elsevier, vol. 124(1), pages 206-213, March.
    18. Yu, Yang & Tang, Jiafu & Sun, Wei & Yin, Yong & Kaku, Ikou, 2013. "Reducing worker(s) by converting assembly line into a pure cell system," International Journal of Production Economics, Elsevier, vol. 145(2), pages 799-806.
    19. Zhang, Yi & Li, Xiaoping & Wang, Qian, 2009. "Hybrid genetic algorithm for permutation flowshop scheduling problems with total flowtime minimization," European Journal of Operational Research, Elsevier, vol. 196(3), pages 869-876, August.
    20. 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.
    21. Mohammad Rostami & Shiva Nikravesh & Mahdi Shahin, 2020. "Minimizing total weighted completion and batch delivery times with machine deterioration and learning effect: a case study from wax production," Operational Research, Springer, vol. 20(3), pages 1255-1287, September.
    22. J. Clausen & M. Perregaard, 1999. "On the best search strategy in parallel branch‐and‐bound:Best‐First Search versus Lazy Depth‐First Search," Annals of Operations Research, Springer, vol. 90(0), pages 1-17, January.
    23. Kathryn E. Stecke & Yong Yin & Ikou Kaku & Yasuhiko Murase, 2012. "Seru: The Organizational Extension of JIT for a Super-Talent Factory," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 3(1), pages 106-119, January.
    24. 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.
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    2. Zhang, Zhe & Song, Xiaoling & Gong, Xue & Yin, Yong & Lev, Benjamin & Zhou, Xiaoyang, 2024. "Coordinated seru scheduling and distribution operation problems with DeJong’s learning effects," European Journal of Operational Research, Elsevier, vol. 313(2), pages 452-464.

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