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Journal of Advanced Transportation
Volume 2017 (2017), Article ID 1527858, 12 pages
https://doi.org/10.1155/2017/1527858
Research Article

A Variable Interval Rescheduling Strategy for Dynamic Flexible Job Shop Scheduling Problem by Improved Genetic Algorithm

1School of Mechanical and Automotive Engineering, Anhui Polytechnic University, Wuhu 241000, China
2Department of Electrical and Computer Engineering, University of Detroit Mercy, Detroit, MI 48221, USA

Correspondence should be addressed to Lei Wang

Received 27 April 2017; Accepted 14 June 2017; Published 19 July 2017

Academic Editor: Rongxin Cui

Copyright © 2017 Lei Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. W. Teekeng and A. Thammano, “Modified genetic algorithm for flexible job-shop scheduling problems,” Procedia Computer Science, vol. 12, no. 12, pp. 122–128, 2012. View at Publisher · View at Google Scholar · View at Scopus
  2. G. Zhang, L. Gao, and Y. Shi, “An effective genetic algorithm for the flexible job-shop scheduling problem,” Expert Systems with Applications, vol. 38, no. 4, pp. 3563–3573, 2011. View at Publisher · View at Google Scholar · View at Scopus
  3. X.-N. Shen and X. Yao, “Mathematical modeling and multi-objective evolutionary algorithms applied to dynamic flexible job shop scheduling problems,” Information Sciences, vol. 298, pp. 198–224, 2015. View at Publisher · View at Google Scholar · View at MathSciNet
  4. P. Fattahi, M. S. Mehrabad, and F. Jolai, “Mathematical modeling and heuristic approaches to flexible job shop scheduling problems,” Journal of Intelligent Manufacturing, vol. 18, no. 3, pp. 331–342, 2007. View at Publisher · View at Google Scholar · View at Scopus
  5. M. R. Garey, D. S. Johnson, and R. Sethi, “The complexity of flowshop and jobshop scheduling,” Mathematics of Operations Research, vol. 1, no. 2, pp. 117–129, 1976. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  6. N. Shivasankaran, P. S. Kumar, and K. V. Raja, “Hybrid sorting immune simulated annealing algorithm for flexible job shop scheduling,” International Journal of Computational Intelligence Systems, vol. 8, no. 3, pp. 455–466, 2015. View at Publisher · View at Google Scholar · View at Scopus
  7. G. Vilcot and J.-C. Billaut, “A tabu search algorithm for solving a multicriteria flexible job shop scheduling problem,” International Journal of Production Research, vol. 49, no. 23, pp. 6963–6980, 2011. View at Publisher · View at Google Scholar · View at Scopus
  8. A. Rossi, “Flexible job shop scheduling with sequence-dependent setup and transportation times by ant colony with reinforced pheromone relationships,” International Journal of Production Economics, vol. 153, pp. 253–267, 2014. View at Publisher · View at Google Scholar · View at Scopus
  9. D. Tang, M. Dai, M. A. Salido, and A. Giret, “Energy-efficient dynamic scheduling for a flexible flow shop using an improved particle swarm optimization,” Computers in Industry, vol. 81, pp. 82–95, 2016. View at Publisher · View at Google Scholar · View at Scopus
  10. L. Wang, G. Zhou, Y. Xu, S. Wang, and M. Liu, “An effective artificial bee colony algorithm for the flexible job-shop scheduling problem,” The International Journal of Advanced Manufacturing Technology, vol. 60, no. 1–4, pp. 303–315, 2012. View at Publisher · View at Google Scholar · View at Scopus
  11. I. Driss, K. N. Mouss, and A. Laggoun, “A new genetic algorithm for flexible job-shop scheduling problems,” Journal of Mechanical Science and Technology, vol. 29, no. 3, pp. 1273–1281, 2015. View at Publisher · View at Google Scholar · View at Scopus
  12. S. H. A. Rahmati, M. Zandieh, and M. Yazdani, “Developing two multi-objective evolutionary algorithms for the multi-objective flexible job shop scheduling problem,” The International Journal of Advanced Manufacturing Technology, vol. 64, no. 5–8, pp. 915–932, 2013. View at Publisher · View at Google Scholar · View at Scopus
  13. J.-Q. Li, Q.-K. Pan, and K.-Z. Gao, “Pareto-based discrete artificial bee colony algorithm for multi-objective flexible job shop scheduling problems,” The International Journal of Advanced Manufacturing Technology, vol. 55, no. 9–12, pp. 1159–1169, 2011. View at Publisher · View at Google Scholar · View at Scopus
  14. L. De Giovanni and F. Pezzella, “An improved genetic algorithm for the distributed and flexible job-shop scheduling problem,” European Journal of Operational Research, vol. 200, no. 2, pp. 395–408, 2010. View at Publisher · View at Google Scholar · View at Scopus
  15. Q. Zhang, H. Manier, and M.-A. Manier, “A genetic algorithm with tabu search procedure for flexible job shop scheduling with transportation constraints and bounded processing times,” Computers & Operations Research, vol. 39, no. 7, pp. 1713–1723, 2012. View at Publisher · View at Google Scholar · View at MathSciNet
  16. G. Zhang, L. Gao, and Y. Shi, “A novel variable neighborhood genetic algorithm for multi-objective flexible job-shop scheduling problems,” Advanced Materials Research, vol. 118-120, pp. 369–373, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. D. Rahmani and R. Ramezanian, “A stable reactive approach in dynamic flexible flow shop scheduling with unexpected disruptions: a case study,” Computers and Industrial Engineering, vol. 98, pp. 360–372, 2016. View at Publisher · View at Google Scholar · View at Scopus
  18. B. Liu, Y. Fan, and Y. Liu, “A fast estimation of distribution algorithm for dynamic fuzzy flexible job-shop scheduling problem,” Computers and Industrial Engineering, vol. 87, pp. 193–201, 2015. View at Publisher · View at Google Scholar · View at Scopus
  19. J. Xiong, L.-N. Xing, and Y.-W. Chen, “Robust scheduling for multi-objective flexible job-shop problems with random machine breakdowns,” International Journal of Production Economics, vol. 141, no. 1, pp. 112–126, 2013. View at Publisher · View at Google Scholar · View at Scopus
  20. N. Al-Hinai and T. Y. Elmekkawy, “Robust and stable flexible job shop scheduling with random machine breakdowns using a hybrid genetic algorithm,” International Journal of Production Economics, vol. 132, no. 2, pp. 279–291, 2011. View at Publisher · View at Google Scholar · View at Scopus
  21. L. Liu, H. Y. Gu, and Y. G. Xi, “Robust and stable scheduling of a single machine with random machine breakdowns,” International Journal of Advanced Manufacturing Technology, vol. 31, no. 7-8, pp. 645–654, 2007. View at Publisher · View at Google Scholar · View at Scopus
  22. F. Zhao, J. Wang, J. Wang, and J. Jonrinaldi, “A dynamic rescheduling model with multi-agent system and its solution method,” Strojniski Vestnik/Journal of Mechanical Engineering, vol. 58, no. 2, pp. 81–92, 2012. View at Publisher · View at Google Scholar · View at Scopus
  23. L. Nie, L. Gao, P. Li, and X. Shao, “Reactive scheduling in a job shop where jobs arrive over time,” Computers and Industrial Engineering, vol. 66, no. 2, pp. 389–405, 2013. View at Publisher · View at Google Scholar · View at Scopus
  24. M. A. Adibi, M. Zandieh, and M. Amiri, “Multi-objective scheduling of dynamic job shop using variable neighborhood search,” Expert Systems with Applications, vol. 37, no. 1, pp. 282–287, 2010. View at Publisher · View at Google Scholar · View at Scopus
  25. P. Fattahi and A. Fallahi, “Dynamic scheduling in flexible job shop systems by considering simultaneously efficiency and stability,” CIRP Journal of Manufacturing Science and Technology, vol. 2, no. 2, pp. 114–123, 2010. View at Publisher · View at Google Scholar · View at Scopus
  26. N. Kundakci and O. Kulak, “Hybrid genetic algorithms for minimizing makespan in dynamic job shop scheduling problem,” Computers and Industrial Engineering, vol. 96, pp. 31–51, 2016. View at Publisher · View at Google Scholar · View at Scopus
  27. E. Ahmadi, M. Zandieh, M. Farrokh, and S. M. Emami, “A multi objective optimization approach for flexible job shop scheduling problem under random machine breakdown by evolutionary algorithms,” Computers and Operations Research, vol. 73, pp. 56–66, 2016. View at Publisher · View at Google Scholar · View at Scopus
  28. X. Qiu and H. Y. K. Lau, “An AIS-based hybrid algorithm with PDRs for multi-objective dynamic online job shop scheduling problem,” Applied Soft Computing Journal, vol. 13, no. 3, pp. 1340–1351, 2013. View at Publisher · View at Google Scholar · View at Scopus
  29. L. Zhang, L. Gao, and X. Li, “A hybrid genetic algorithm and tabu search for a multi-objective dynamic job shop scheduling problem,” International Journal of Production Research, vol. 51, no. 12, pp. 3516–3531, 2013. View at Publisher · View at Google Scholar · View at Scopus
  30. A. A. R. Hosseinabadi, H. Siar, S. Shamshirband, M. Shojafar, and M. H. N. Md. Nasir, “Using the gravitational emulation local search algorithm to solve the multi-objective flexible dynamic job shop scheduling problem in Small and Medium Enterprises,” Annals of Operations Research, vol. 229, no. 1, pp. 451–474, 2014. View at Publisher · View at Google Scholar · View at Scopus
  31. M.-S. Lu and R. Romanowski, “Multicontextual dispatching rules for job shops with dynamic job arrival,” International Journal of Advanced Manufacturing Technology, vol. 67, no. 1-4, pp. 19–33, 2013. View at Publisher · View at Google Scholar · View at Scopus
  32. H. Karimi, S. H. A. Rahmati, and M. Zandieh, “An efficient knowledge-based algorithm for the flexible job shop scheduling problem,” Knowledge-Based Systems, vol. 36, no. 6, pp. 236–244, 2012. View at Publisher · View at Google Scholar · View at Scopus
  33. Z. Wu, H. He, and C. Huang, “Flexible job shop dynamic scheduling problem research with machine fault [J],” Machine Design and Research, vol. 31, no. 3, pp. 94–98, 2015. View at Google Scholar
  34. I. Kacem, S. Hammadi, and P. Borne, “Approach by localization and multiobjective evolutionary optimization for flexible job-shop scheduling problems,” IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, vol. 32, no. 1, pp. 1–13, 2002. View at Publisher · View at Google Scholar · View at Scopus
  35. J. Tang, G. Zhang, B. Lin, and B. Zhang, “A hybrid algorithm for flexible job-shop scheduling problem,” Procedia Engineering, vol. 15, no. 1, pp. 3678–3683, 2011. View at Google Scholar
  36. X. Li and L. Gao, “An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem,” International Journal of Production Economics, vol. 174, pp. 93–110, 2016. View at Publisher · View at Google Scholar · View at Scopus