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Mathematical Problems in Engineering
Volume 2016, Article ID 1679315, 9 pages
http://dx.doi.org/10.1155/2016/1679315
Research Article

Enhanced Simulated Annealing for Solving Aggregate Production Planning

1Department of Mathematics, Faculty of Science, Universiti Putra Malaysia, Malaysia
2Department of Statistics, Faculty of Administration and Economics, University of Baghdad, Baghdad, Iraq
3Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, Universiti Putra Malaysia, Malaysia

Received 28 March 2016; Accepted 11 July 2016

Academic Editor: Sergii V. Kavun

Copyright © 2016 Mohd Rizam Abu Bakar 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. C. C. Holt, F. Modigliani, and H. A. Simon, “A linear decision rule for production and employment scheduling,” Management Science, vol. 2, no. 1, pp. 1–30, 1955. View at Publisher · View at Google Scholar
  2. G. L. Bergstrom and B. E. Smith, “Multi-item production planning-an extension of the hmms rules,” Management Science, vol. 16, no. 10, pp. 614–629, 1970. View at Publisher · View at Google Scholar · View at Scopus
  3. G. R. Bitran and H. H. Yanasse, “Deterministic approximations to stochastic production problems,” Operations Research, vol. 32, no. 5, pp. 999–1018, 1984. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  4. S.-J. Nam and R. Logendran, “Aggregate production planning—a survey of models and methodologies,” European Journal of Operational Research, vol. 61, no. 3, pp. 255–272, 1992. View at Publisher · View at Google Scholar · View at Scopus
  5. O. S. Silva Filho, “An aggregate production planning model with demand under uncertainty,” Production Planning & Control, vol. 10, no. 8, pp. 745–756, 1999. View at Publisher · View at Google Scholar · View at Scopus
  6. R. Y. Fung, J. Tang, and D. Wang, “Multiproduct aggregate production planning with fuzzy demands and fuzzy capacities,” IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans., vol. 33, no. 3, pp. 302–313, 2003. View at Publisher · View at Google Scholar · View at Scopus
  7. S. M. J. Mirzapour Al-E-Hashem, H. Malekly, and M. B. Aryanezhad, “A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty,” International Journal of Production Economics, vol. 134, no. 1, pp. 28–42, 2011. View at Publisher · View at Google Scholar · View at Scopus
  8. R. Zhang, L. Zhang, Y. Xiao, and I. Kaku, “The activity-based aggregate production planning with capacity expansion in manufacturing systems,” Computers and Industrial Engineering, vol. 62, no. 2, pp. 491–503, 2012. View at Publisher · View at Google Scholar · View at Scopus
  9. A. Jamalnia and A. Feili, “A simulation testing and analysis of aggregate production planning strategies,” Production Planning and Control, vol. 24, no. 6, pp. 423–448, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. F. Tonelli, M. Paolucci, D. Anghinolfi, and P. Taticchi, “Production planning of mixed-model assembly lines: a heuristic mixed integer programming based approach,” Production Planning and Control, vol. 24, no. 1, pp. 110–127, 2013. View at Publisher · View at Google Scholar · View at Scopus
  11. N. Gholamian, I. Mahdavi, and R. Tavakkoli-Moghaddam, “Multi-objective multi-product multi-site aggregate production planning in a supply chain under uncertainty: fuzzy multi-objective optimisation,” International Journal of Computer Integrated Manufacturing, vol. 29, no. 2, pp. 149–165, 2016. View at Publisher · View at Google Scholar · View at Scopus
  12. A. Baykasoglu and T. Gocken, “Multi-objective aggregate production planning with fuzzy parameters,” Advances in Engineering Software, vol. 41, no. 9, pp. 1124–1131, 2010. View at Publisher · View at Google Scholar · View at Scopus
  13. M. Ramazanian and A. Modares, “Application of particle swarm optimization algorithm to aggregate production planning,” Asian Journal of Business Management Studies, vol. 2, no. 2, pp. 44–54, 2011. View at Google Scholar
  14. D. Wang and S.-C. Fang, “A genetics-based approach for aggregated production planning in a fuzzy environment,” IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans, vol. 27, no. 5, pp. 636–645, 1997. View at Publisher · View at Google Scholar · View at Scopus
  15. G. M. Kumar and A. N. Haq, “Hybrid genetic—ant colony algorithms for solving aggregate production plan,” Journal of Advanced Manufacturing Systems, vol. 4, no. 1, pp. 103–111, 2005. View at Publisher · View at Google Scholar · View at Scopus
  16. P. Aungkulanon, B. Phruksaphanrat, and P. Luangpaiboon, “Harmony search algorithm with various evolutionary elements for fuzzy aggregate production planning,” in Intelligent Control and Innovative Computing, S. I. Ao, O. Castillo, and X. Huang, Eds., vol. 110 of Lecture Notes in Electrical Engineering, pp. 189–201, Springer, Berlin, Germany, 2012. View at Publisher · View at Google Scholar
  17. P. Luangpaiboon and P. Aungkulanon, “Integrated approaches to enhance aggregate production planning with inventory uncertainty based on improved harmony search algorithm,” Proceedings of World Academy of Science, Engineering and Technology, no. 73, p. 243, 2013. View at Google Scholar
  18. M. Kaveh and V. M. Dalfard, “A simulated annealing algorithm for aggregate production planning with considering of ancillary costs,” International Journal of Mathematics in Operational Research, vol. 6, no. 4, pp. 474–490, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  19. S.-C. Wang and M.-F. Yeh, “A modified particle swarm optimization for aggregate production planning,” Expert Systems with Applications, vol. 41, no. 6, pp. 3069–3077, 2014. View at Publisher · View at Google Scholar · View at Scopus
  20. R. Ramezanian, D. Rahmani, and F. Barzinpour, “An aggregate production planning model for two phase production systems: solving with genetic algorithm and tabu search,” Expert Systems with Applications, vol. 39, no. 1, pp. 1256–1263, 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. Z. W. Geem, J. H. Kim, and G. V. Loganathan, “A new heuristic optimization algorithm: harmony search,” Simulation, vol. 76, no. 2, pp. 60–68, 2001. View at Publisher · View at Google Scholar · View at Scopus
  22. S. Kirkpatrick, J. Gelatt, and M. P. Vecchi, “Optimization by simulated annealing,” Science, vol. 220, no. 4598, pp. 671–680, 1983. View at Publisher · View at Google Scholar · View at MathSciNet
  23. V. M. Dalfard and G. Mohammadi, “Two meta-heuristic algorithms for solving multi-objective flexible job-shop scheduling with parallel machine and maintenance constraints,” Computers and Mathematics with Applications, vol. 64, no. 6, pp. 2111–2117, 2012. View at Publisher · View at Google Scholar · View at Scopus