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Scientific Programming
Volume 2016, Article ID 8264879, 9 pages
http://dx.doi.org/10.1155/2016/8264879
Research Article

A Recovery Model for Production Scheduling: Combination of Disruption Management and Internet of Things

1School of Light Industry & Chemical Engineering, Dalian Polytechnic University, Dalian 116034, China
2School of Business Administration, Dongbei University of Finance and Economics, Dalian 116025, China

Received 13 June 2016; Accepted 25 August 2016

Academic Editor: Chengyan Yue

Copyright © 2016 Yang Jiang 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. H. Aytug, M. A. Lawley, K. McKay, S. Mohan, and R. Uzsoy, “Executing production schedules in the face of uncertainties: a review and some future directions,” European Journal of Operational Research, vol. 161, no. 1, pp. 86–110, 2005. View at Publisher · View at Google Scholar · View at Scopus
  2. M. Z. Liu, H. Shan, Z. Q. Jiang, M. Ge, J. Hu, and M. Zhang, “Dynamic rescheduling optimization of job-shop under uncertain conditions,” Journal of Mechanical Engineering, vol. 45, no. 10, pp. 137–142, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. X. Qi, J. F. Bard, and G. Yu, “Disruption management for machine scheduling: the case of SPT schedules,” International Journal of Production Economics, vol. 103, no. 1, pp. 166–184, 2006. View at Publisher · View at Google Scholar · View at Scopus
  4. G. Yu and X. Qi, Disruption Management: Framework, Models and Applications, World Scientific Publishing Company Incorporated, 2004.
  5. M. Løve, K. R. Sørensen, J. Larsen, and J. Clausen, “Disruption management for an airline—rescheduling of aircraft,” in Applications of Evolutionary Computing, S. Cagnoni, J. Gottlieb, E. Hart, M. Middendorf, and G. R. Raidl, Eds., vol. 2279 of Lecture Notes in Computer Science, pp. 315–324, Springer, Berlin, Germany, 2002. View at Publisher · View at Google Scholar
  6. G. Yu, M. Argüello, G. Song, S. M. McCowan, and A. White, “A new era for crew recovery at continental airlines,” Interfaces, vol. 33, no. 1, pp. 5–22, 2003. View at Publisher · View at Google Scholar · View at Scopus
  7. C.-Y. Lee and G. Yu, “Parallel-machine scheduling under potential disruption,” Optimization Letters, vol. 2, no. 1, pp. 27–37, 2008. View at Publisher · View at Google Scholar · View at Scopus
  8. L. Tang and Y. Zhang, “Parallel machine scheduling under the disruption of machine breakdown,” Industrial & Engineering Chemistry Research, vol. 48, no. 14, pp. 6660–6667, 2009. View at Publisher · View at Google Scholar · View at Scopus
  9. J.-J. Wang, J.-B. Wang, and F. Liu, “Parallel machines scheduling with a deteriorating maintenance activity,” Journal of the Operational Research Society, vol. 62, no. 10, pp. 1898–1902, 2011. View at Publisher · View at Google Scholar · View at Scopus
  10. F. Liu, J.-J. Wang, and D.-L. Yang, “Solving single machine scheduling under disruption with discounted costs by quantum-inspired hybrid heuristics,” Journal of Manufacturing Systems, vol. 32, no. 4, pp. 715–723, 2013. View at Publisher · View at Google Scholar · View at Scopus
  11. U. K. Khedlekar, D. Shukla, and R. P. S. Chandel, “Computational study for disrupted production system with time dependent demand,” Journal of Scientific & Industrial Research, vol. 73, no. 5, pp. 294–301, 2014. View at Google Scholar
  12. S. K. Paul, R. Sarker, and D. Essam, “Managing disruption in an imperfect production–inventory system,” Computers & Industrial Engineering, vol. 84, pp. 101–112, 2015. View at Publisher · View at Google Scholar · View at Scopus
  13. R. Sarker, D. Essam, S. M. K. Hasan, and A. N. M. Karim, “Managing risk in production scheduling under uncertain disruption,” Artificial Intelligence for Engineering Design, Analysis and Manufacturing, vol. 30, no. 3, pp. 289–299, 2016. View at Publisher · View at Google Scholar · View at Scopus
  14. E. Bendoly, K. Donohue, and K. L. Schultz, “Behavior in operations management: assessing recent findings and revisiting old assumptions,” Journal of Operations Management, vol. 24, no. 6, pp. 737–752, 2006. View at Publisher · View at Google Scholar · View at Scopus
  15. C. H. Loch and Y. Wu, Behavioral Operations Management, Now Publishers Inc, 2007.
  16. X. Su, “Bounded rationality in newsvendor models,” Manufacturing & Service Operations Management, vol. 10, no. 4, pp. 566–589, 2008. View at Publisher · View at Google Scholar · View at Scopus
  17. F. Gino and G. Pisano, “Toward a theory of behavioral operations,” Manufacturing & Service Operations Management, vol. 10, no. 4, pp. 676–691, 2008. View at Publisher · View at Google Scholar · View at Scopus
  18. Y. Chen, X. Su, and X. Zhao, “Modeling bounded rationality in capacity allocation games with the quantal response equilibrium,” Management Science, vol. 58, no. 10, pp. 1952–1962, 2012. View at Publisher · View at Google Scholar · View at Scopus
  19. K. V. Katsikopoulos and G. Gigerenzer, “Behavioral operations management: a blind spot and a research program,” Journal of Supply Chain Management, vol. 49, no. 1, pp. 3–7, 2013. View at Publisher · View at Google Scholar · View at Scopus
  20. Y. Chen and X. Zhao, “Decision bias in capacity allocation games with uncertain demand,” Production and Operations Management, vol. 24, no. 4, pp. 634–646, 2015. View at Publisher · View at Google Scholar · View at Scopus
  21. D. Kahneman and A. Tversky, “Prospect theory: an analysis of decision under risk,” Econometrica, vol. 47, no. 2, pp. 263–292, 1979. View at Publisher · View at Google Scholar
  22. Q. L. Ding, X. P. Hu, and Y. Jiang, “A model of disruption management based on prospect theory in logistic distribution,” Journal of Management Sciences in China, vol. 17, no. 11, pp. 1–9, 2014. View at Google Scholar
  23. A. Colorni, M. Dorigo, and V. Maniezzo, “Distributed optimization by ant colonies,” in Proceedings of the European Conference on Artificial Life, pp. 134–142, Paris, France, 1991.
  24. S. R. Balseiro, I. Loiseau, and J. Ramonet, “An Ant Colony algorithm hybridized with insertion heuristics for the time dependent vehicle routing problem with time windows,” Computers & Operations Research, vol. 38, no. 6, pp. 954–966, 2011. View at Publisher · View at Google Scholar · View at Scopus
  25. R.-H. Huang, C.-L. Yang, and W.-C. Cheng, “Flexible job shop scheduling with due window—a two-pheromone ant colony approach,” International Journal of Production Economics, vol. 141, no. 2, pp. 685–697, 2013. View at Publisher · View at Google Scholar · View at Scopus
  26. M. Faisal, H. Mathkour, and M. Alsulaiman, “AntStar: enhancing optimization problems by integrating an ant system and A algorithm,” Scientific Programming, vol. 2016, Article ID 5136327, 12 pages, 2016. View at Publisher · View at Google Scholar
  27. É. D. Taillard, “Parallel taboo search techniques for the job shop scheduling problem,” INFORMS Journal on Computing, vol. 6, no. 2, pp. 108–117, 1994. View at Publisher · View at Google Scholar
  28. E. Demirkol, S. Mehta, and R. Uzsoy, “A computational study of shifting bottleneck procedures for shop scheduling problems,” Journal of Heuristics, vol. 3, no. 2, pp. 111–137, 1997. View at Publisher · View at Google Scholar · View at Scopus
  29. E. Nowicki and C. Smutnicki, “An advanced tabu search algorithm for the job shop problem,” Journal of Scheduling, vol. 8, no. 2, pp. 145–159, 2005. View at Publisher · View at Google Scholar · View at Scopus
  30. P. M. Pardalos and O. V. Shylo, “An algorithm for the job shop scheduling problem based on global equilibrium search techniques,” Computational Management Science, vol. 3, no. 4, pp. 331–348, 2006. View at Publisher · View at Google Scholar · View at Scopus
  31. P. M. Pardalos, O. V. Shylo, and A. Vazacopoulos, “Solving job shop scheduling problems utilizing the properties of backbone and ‘big valley’,” Computational Optimization and Applications, vol. 47, no. 1, pp. 61–76, 2010. View at Publisher · View at Google Scholar · View at Scopus
  32. A. Tversky and D. Kahneman, “Advances in prospect theory: cumulative representation of uncertainty,” Journal of Risk and Uncertainty, vol. 5, no. 4, pp. 297–323, 1992. View at Publisher · View at Google Scholar · View at Scopus
  33. R. J. Abumaizar and J. A. Svestka, “Rescheduling job shops under random disruptions,” International Journal of Production Research, vol. 35, no. 7, pp. 2065–2082, 1997. View at Publisher · View at Google Scholar · View at Scopus