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Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 3938679, 10 pages
http://dx.doi.org/10.1155/2016/3938679
Research Article

A Hybrid Algorithm Based on Particle Swarm Optimization and Artificial Immune for an Assembly Job Shop Scheduling Problem

1Department of IE, Tsinghua University, Beijing 100084, China
2Department of Mechanical Electronic Engineering, Zaozhuang University, Zaozhuang 277160, China
3Mechanical and Electrical Technology Research Center, Zhejiang Normal University, Jinhua 321004, China

Received 30 April 2016; Accepted 10 July 2016

Academic Editor: Roberto Dominguez

Copyright © 2016 Hui Du 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. J. W. Barnes and J. B. Chambers, “Solving the job shop scheduling problem with tabu search,” IIE Transactions, vol. 27, no. 2, pp. 257–263, 1995. View at Google Scholar · View at Scopus
  2. P. Fattahi, S. M. Hosseini, F. Jolai, and R. Tavakkoli-Moghaddam, “A branch and bound algorithm for hybrid flow shop scheduling problem with setup time and assembly operations,” Applied Mathematical Modelling. Simulation and Computation for Engineering and Environmental Systems, vol. 38, no. 1, pp. 119–134, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  3. Y. Tian, D. Liu, D. Yuan, and K. Wang, “A discrete PSO for two-stage assembly scheduling problem,” International Journal of Advanced Manufacturing Technology, vol. 66, no. 1–4, pp. 481–499, 2013. View at Publisher · View at Google Scholar · View at Scopus
  4. C. S. Sung and H. A. Kim, “A two-stage multiple-machine assembly scheduling problem for minimizing sum of completion times,” International Journal of Production Economics, vol. 113, no. 2, pp. 1038–1048, 2008. View at Publisher · View at Google Scholar · View at Scopus
  5. E. Shokrollahpour, M. Zandieh, and B. Dorri, “A novel imperialist competitive algorithm for bi-criteria scheduling of the assembly flowshop problem,” International Journal of Production Research, vol. 49, no. 11, pp. 3087–3103, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. H. Seidgar, M. Kiani, M. Abedi, and H. Fazlollahtabar, “An efficient imperialist competitive algorithm for scheduling in the two-stage assembly flow shop problem,” International Journal of Production Research, vol. 52, no. 4, pp. 1240–1256, 2014. View at Publisher · View at Google Scholar · View at Scopus
  7. G. M. Komaki and V. Kayvanfar, “Grey Wolf Optimizer algorithm for the two-stage assembly flow shop scheduling problem with release time,” Journal of Computational Science, vol. 8, pp. 109–120, 2015. View at Publisher · View at Google Scholar · View at Scopus
  8. C.-J. Liao, C.-H. Lee, and H.-C. Lee, “An efficient heuristic for a two-stage assembly scheduling problem with batch setup times to minimize makespan,” Computers and Industrial Engineering, vol. 88, pp. 317–325, 2015. View at Publisher · View at Google Scholar · View at Scopus
  9. H.-S. Yan, X.-Q. Wan, and F.-L. Xiong, “A hybrid electromagnetism-like algorithm for two-stage assembly flow shop scheduling problem,” International Journal of Production Research, vol. 52, no. 19, pp. 5626–5639, 2014. View at Publisher · View at Google Scholar · View at Scopus
  10. A. Mozdgir, S. M. T. Fatemi Ghomi, F. Jolai, and J. Navaei, “Two-stage assembly flow-shop scheduling problem with non-identical assembly machines considering setup times,” International Journal of Production Research, vol. 51, no. 12, pp. 3625–3642, 2013. View at Publisher · View at Google Scholar · View at Scopus
  11. J. K. Lenstra, A. H. Rinnooy Kan, and P. Brucker, “Complexity of machine scheduling problems,” in Annals of Discrete Mathematics, vol. 1 of Studies in Integer Programming, pp. 343–362, North-Holland, Amsterdam, Netherlands, 1977. View at Publisher · View at Google Scholar · View at MathSciNet
  12. F.-J. Wang, G.-K. Zhao, Z.-Y. Jia, X.-H. Lu, and L.-P. Wang, “Assembly job shop scheduling based on feasible solution space genetic algorithm,” Computer Integrated Manufacturing Systems, vol. 16, no. 1, pp. 115–120, 2010. View at Google Scholar · View at Scopus
  13. T. C. Wong and S. C. Ngan, “A comparison of hybrid genetic algorithm and hybrid particle swarm optimization to minimize makespan for assembly job shop,” Applied Soft Computing Journal, vol. 13, no. 3, pp. 1391–1399, 2013. View at Publisher · View at Google Scholar · View at Scopus
  14. F. S. Al-Anzi and A. Allahverdi, “An artificial immune system heuristic for two-stage multi-machine assembly scheduling problem to minimize total completion time,” Journal of Manufacturing Systems, vol. 32, no. 4, pp. 825–830, 2013. View at Publisher · View at Google Scholar · View at Scopus
  15. F. S. Al-Anzi and A. Allahverdi, “Better heuristics for a two-stage multi-machine assembly scheduling problem to minimize total completion time,” International Journal of Operations Research, vol. 9, no. 2, pp. 66–75, 2012. View at Google Scholar · View at MathSciNet
  16. J. Xu and R. Nagi, “Solving assembly scheduling problems with tree-structure precedence constraints: a Lagrangian relaxation approach,” IEEE Transactions on Automation Science and Engineering, vol. 10, no. 3, pp. 757–771, 2013. View at Publisher · View at Google Scholar · View at Scopus
  17. G. M. Komaki, E. Teymourian, and V. Kayvanfar, “Minimising makespan in the two-stage assembly hybrid flow shop scheduling problem using artificial immune systems,” International Journal of Production Research, vol. 54, no. 4, pp. 963–983, 2015. View at Publisher · View at Google Scholar
  18. R. C. Eberhart and J. Kennedy, “New optimizer using particle swarm theory,” in Proceedings of the 1995 6th International Symposium on Micro Machine and Human Science, pp. 39–43, IEEE Service Center, Nagoya, Japan, October 1995. View at Scopus
  19. J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proceedings of the 1995 IEEE International Conference on Neural Networks, pp. 1942–1948, Washington, DC, USA, December 1995. View at Scopus
  20. A. Jamili, M. A. Shafia, and R. Tavakkoli-Moghaddam, “A hybrid algorithm based on particle swarm optimization and simulated annealing for a periodic job shop scheduling problem,” International Journal of Advanced Manufacturing Technology, vol. 54, no. 1–4, pp. 309–322, 2011. View at Publisher · View at Google Scholar · View at Scopus
  21. W.-J. Xia and Z.-M. Wu, “A hybrid particle swarm optimization approach for the job-shop scheduling problem,” International Journal of Advanced Manufacturing Technology, vol. 29, no. 3-4, pp. 360–366, 2006. View at Publisher · View at Google Scholar · View at Scopus
  22. Y. Shi and R. Eberhart, “A modified particle swarm optimizer,” in Proceedings of the IEEE World Congress on Computational Intelligence, pp. 69–73, Anchorage, Alaska, USA, May 1998. View at Publisher · View at Google Scholar
  23. L. N. De Castro and J. Timmis, Artificial Immune Systems: A New Computational Intelligence Approach, Springer, New York, NY, USA, 2002.
  24. E. Hart and J. Timmis, “Application areas of AIS: the past, the present and the future,” Applied Soft Computing Journal, vol. 8, no. 1, pp. 191–201, 2008. View at Publisher · View at Google Scholar · View at Scopus
  25. Benchmark Models, http://amsterdamoptimization.com/benchmarkmodels.html.
  26. J. Xu, S.-M. Fei, S.-Y. Zhang, and Y.-D. Shi, “Adaptive particle swarm optimization for the project scheduling problem with dynamic allocation of resource,” Computer Integrated Manufacturing Systems, vol. 17, no. 8, pp. 1790–1797, 2011. View at Google Scholar · View at Scopus