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Dynamic Job Shop Scheduling Problem with New Job Arrivals: A Survey

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Proceedings of 2019 Chinese Intelligent Automation Conference (CIAC 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 586))

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Abstract

To meet the increasingly changing market environment, necessary dynamic scheduling is needed for modern manufacturing enterprises to handle real time events, such as machine breakdowns, job arrivals, and due date changing, etc. This paper focuses on dynamic scheduling problem in job shops with new job arrivals. Firstly, the definition of dynamic job shop scheduling problem (JSP) is introduced. Then, a framework of dynamic scheduling is described in a comprehensive way, including strategies, policies, methods and solution approaches. Then, a survey of the latest literature on dynamic JSP with new job arrivals is provided. Lastly, a brief discussion on relevant literature is presented.

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References

  1. Holloway CA, Nelson RT (1974) Job shop scheduling with due dates and variable processing times. Manag Sci 20(9):1264–1275

    Article  MATH  Google Scholar 

  2. Nelson R, Holloway C, Wong RML (1977) Centralized scheduling and priority implementation heuristics for a dynamic job shop model. AIIE Trans 9(1):95–102

    Article  Google Scholar 

  3. Ouelhadj D, Petrovic S (2009) A survey of dynamic scheduling in manufacturing systems. J Sched 12(4):417–431

    Article  MathSciNet  MATH  Google Scholar 

  4. Ramasesh R (1990) Dynamic job shop scheduling: a survey of simulation research. Omega 18(1):43–57

    Article  Google Scholar 

  5. Suresh V, Chaudhuri D (1993) Dynamic scheduling—a survey of research. Int J Prod Econ 32(1):53–63

    Article  Google Scholar 

  6. Vieira GE, Herrmann JW, Lin E (2003) Rescheduling manufacturing systems: a framework of strategies, policies, and methods. J Sched 6(1):39–62

    Article  MathSciNet  MATH  Google Scholar 

  7. Potts CN, Strusevich VA (2009) Fifty years of scheduling: a survey of milestones. J Oper Res Soc 60(1):41–68

    Article  MATH  Google Scholar 

  8. Yamamoto M, Nof SY (1985) Scheduling/rescheduling in the manufacturing operating system environment. Int J Prod Res 23(4):705–722

    Article  Google Scholar 

  9. Church LK, Uzsoy R (1992) Analysis of periodic and event-driven rescheduling policies in dynamic shops. Int J Comput Integr Manuf 5(3):153–163

    Article  Google Scholar 

  10. Li RK, Shyu YT, Adiga S (1993) Heuristic rescheduling algorithm for computer-based production scheduling systems. Int J Prod Res 31(8):1815–1826

    Article  Google Scholar 

  11. Kim MH, Kim YD (1994) Simulation-based real-time scheduling in a flexible manufacturing system. J. Manuf. Syst. 13(2):85–93

    Article  MathSciNet  Google Scholar 

  12. Abumaizar RJ, Svestka JA (1997) Rescheduling job shops under random disruptions. Int J Prod Res 35(7):2065–2082

    Article  MATH  Google Scholar 

  13. Jain AK, Elmaraghy HA (1997) Production scheduling/rescheduling in flexible manufacturing. Int J Prod Res 35(1):281–309

    Article  MATH  Google Scholar 

  14. Bean JC, Birge JR, Mittenthal J, Noon CE (1991) Matchup scheduling with multiple resources, release dates and disruptions. Oper Res 39(3):470–483

    Article  MATH  Google Scholar 

  15. Gomes MC, Barbosa-Póvoa AP, Novais AQ (2010) A discrete time reactive scheduling model for new order insertion in job shop, make-to-order industries. Int J Prod Res 48(24):7395–7422

    Article  MATH  Google Scholar 

  16. Gao KZ, Suganthan PN, Chua TJ, Chong CS, Cai TX, Pan QK (2015) A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion. Expert Syst Appl 42(21):7652–7663

    Article  Google Scholar 

  17. Petrovic D, Duenas A (2006) A fuzzy logic based production scheduling/rescheduling in the presence of uncertain disruptions. Fuzzy Sets Syst 157(16):2273–2285

    Article  MathSciNet  MATH  Google Scholar 

  18. Cowling P, Johansson M (2002) Using real time information for effective dynamic scheduling. Eur J Oper Res 139(2):230–244

    Article  MathSciNet  MATH  Google Scholar 

  19. Liu W, Jin Y, Price M (2017) New scheduling algorithms and digital tool for dynamic permutation flowshop with newly arrived order. Int J Prod Res 55(11):3234–3248

    Article  Google Scholar 

  20. Gao KZ, Suganthan PN, Tasgetiren MF, Pan QK, Sun QQ (2015) Effective ensembles of heuristics for scheduling flexible job shop problem with new job insertion. Comput Ind Eng 90:107–117

    Article  Google Scholar 

  21. Li N, Liang G, Li P, Shao X (2013) Reactive scheduling in a job shop where jobs arrive over time. Comput Ind Eng 66(2):389–405

    Article  Google Scholar 

  22. Muhlemann AP, Lockett AG, Farn CK (1982) Job shop scheduling heuristics and frequency of scheduling. Int J Prod Res 20(2):227–241

    Article  Google Scholar 

  23. Sabuncuoglu I, Bayiz M (2000) Analysis of reactive scheduling problems in a job shop environment. Eur J Oper Res 126(3):567–586

    Article  MATH  Google Scholar 

  24. Dominic PDD, Kaliyamoorthy S, Kumar MS (2004) Efficient dispatching rules for dynamic job shop scheduling. Int J Adv Manuf Technol 24(1–2):70–75

    Google Scholar 

  25. Lu MS, Romanowski R (2013) Multicontextual dispatching rules for job shops with dynamic job arrival. Int J Adv Manuf Technol 67(1–4):19–33

    Article  Google Scholar 

  26. Gunasekaran A, Goyal SK, Martikainen T, Yli-Olli P (1994) Economic scheduling of a new order in a job-shop production system. Int J Syst Sci 25(2):365–376

    Article  MathSciNet  MATH  Google Scholar 

  27. Chang FCR (1997) Heuristics for dynamic job shop scheduling with real-time updated queueing time estimates. Int J Prod Res 35(3):651–665

    Article  MathSciNet  MATH  Google Scholar 

  28. Kis T, Hertz A (2003) A lower bound for the job insertion problem. Discret Appl Math 128(2):395–419

    Article  MathSciNet  MATH  Google Scholar 

  29. Fattahi P, Fallahi A (2010) Dynamic scheduling in flexible job shop systems by considering simultaneously efficiency and stability. CIRP J Manuf Sci Technol 2(2):114–123

    Article  Google Scholar 

  30. Moratori P, Petrovic S, Vázquez-Rodríguez J (2010) Integrating rush orders into existent schedules for a complex job shop problem. Appl Intell 32(2):205–215

    Article  Google Scholar 

  31. Moratori P, Petrovic S (2012) Match-up approaches to a dynamic rescheduling problem. Int J Prod Res 50(1):261–276

    Article  Google Scholar 

  32. Gao KZ, Suganthan PN, Pan QK, Tasgetiren MF, Sadollah A (2016) Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion. Knowl-Based Syst 109:1–16

    Article  Google Scholar 

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Acknowledgments

This research is supported by the Natural Science Foundation of China under Grant No. 61673228, 61703220 and 61402216, the Natural Science Foundation of Shandong Province under Grant No. ZR2010GM006.

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Authors and Affiliations

  1. Institute of Complexity Science, College of Automation, Qingdao University, Qingdao, 266071, China

    Zhen Wang & Jihui Zhang

  2. College of Electrical Engineering, Qingdao University, Qingdao, 266071, China

    Zhen Wang

  3. Naval Aeronautical Engineering Institute Qingdao Branch, Qingdao, 266041, China

    Jianfei Si

Authors
  1. Zhen Wang
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  2. Jihui Zhang
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  3. Jianfei Si
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Corresponding author

Correspondence to Zhen Wang .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Zhidong Deng

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Wang, Z., Zhang, J., Si, J. (2020). Dynamic Job Shop Scheduling Problem with New Job Arrivals: A Survey. In: Deng, Z. (eds) Proceedings of 2019 Chinese Intelligent Automation Conference. CIAC 2019. Lecture Notes in Electrical Engineering, vol 586. Springer, Singapore. https://doi.org/10.1007/978-981-32-9050-1_75

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