Table of Contents Author Guidelines Submit a Manuscript
Journal of Applied Mathematics
Volume 2013 (2013), Article ID 451090, 15 pages
http://dx.doi.org/10.1155/2013/451090
Research Article

Shuffled Frog Leaping Algorithm for Preemptive Project Scheduling Problems with Resource Vacations Based on Patterson Set

1School of Management, Huazhong University of Science and Technology, Wuhan 430074, China
2College of Economics and Management, Zhejiang University of Technology, Hangzhou 310023, China
3Technological Innovation and Enterprise Internationalization Research Center, Zhejiang Provincial Key Research Institute of Philosophy & Social Sciences, Hangzhou 310023, China
4Department of Environmental and Information Studies, Tokyo City University, Yokohama 224-0015, Japan
5School of Logistics, Southwest Jiaotong University, Chengdu 610031, China

Received 24 July 2013; Revised 29 August 2013; Accepted 30 August 2013

Academic Editor: Sabri Arik

Copyright © 2013 Yi Han 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. X. Wang and W. Huang, “Fuzzy resource-constrained project scheduling problem for software development,” Wuhan University Journal of Natural Sciences, vol. 15, no. 1, pp. 25–30, 2010. View at Publisher · View at Google Scholar · View at Scopus
  2. L. Yan, B. Jinsong, H. Xiaofeng, and J. Ye, “A heuristic project scheduling approach for quick response to maritime disaster rescue,” International Journal of Project Management, vol. 27, no. 6, pp. 620–628, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. C. Bai, M. Gershon, and X. Wei, “Fuzzy critical chain method based on genetic algorithm for project scheduling,” Information B, vol. 13, no. 3, pp. 877–892, 2010. View at Google Scholar · View at Scopus
  4. C. Bai, M. Gershon, and X. Wei, “Comparison of fuzzy buffer size algorithms in critical chain scheduling,” Information B, vol. 13, no. 3, pp. 893–903, 2010. View at Google Scholar · View at Scopus
  5. M. Mobini, Z. Mobini, and M. Rabbani, “An Artificial Immune Algorithm for the project scheduling problem under resource constraints,” Applied Soft Computing Journal, vol. 11, no. 2, pp. 1975–1982, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. A. Agarwal, S. Colak, and S. Erenguc, “A Neurogenetic approach for the resource-constrained project scheduling problem,” Computers and Operations Research, vol. 38, no. 1, pp. 44–50, 2011. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  7. H. Zhang, H. Li, and C. M. Tam, “Particle swarm optimization for resource-constrained project scheduling,” International Journal of Project Management, vol. 24, no. 1, pp. 83–92, 2006. View at Publisher · View at Google Scholar · View at Scopus
  8. X. Pan and L. Jiao, “Multi-agent social evolutionary algorithm for project optimization scheduling,” Journal of Computer Research and Development, vol. 45, no. 6, pp. 998–1003, 2008. View at Google Scholar · View at Scopus
  9. J. Gonçalves, J. Mendes, and M. Resende, “A genetic algorithm for the resource constrained multi-project scheduling problem,” European Journal of Operational Research, vol. 189, no. 3, pp. 1171–1190, 2008. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  10. Y. Xu, L. Wang, and Y. Yang, “Dynamic vehicle routing using an improved variable neighborhood search algorithm,” Journal of Applied Mathematics, vol. 2013, Article ID 672078, 12 pages, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  11. S. L. Tilahun and H. C. Ong, “Modified firefly algorithm,” Journal of Applied Mathematics, vol. 2012, Article ID 467631, 12 pages, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  12. L. Zhang, Y. Xu, and Y. Liu, “An elite decision making harmony search algorithm for optimization problem,” Journal of Applied Mathematics, vol. 2012, Article ID 860681, 15 pages, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  13. L. Yan, B. Jinsong, H. Xiaofeng, and J. Ye, “A heuristic project scheduling approach for quick response to maritime disaster rescue,” International Journal of Project Management, vol. 27, no. 6, pp. 620–628, 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. D. Golenko-Ginzburg and A. Gonik, “A heuristic for network project scheduling with random activity durations depending on the resource allocation,” International Journal of Production Economics, vol. 55, no. 2, pp. 149–162, 1998. View at Publisher · View at Google Scholar · View at Scopus
  15. H. Chtourou and M. Haouari, “A two-stage-priority-rule-based algorithm for robust resource-constrained project scheduling,” Computers and Industrial Engineering, vol. 55, no. 1, pp. 183–194, 2008. View at Publisher · View at Google Scholar · View at Scopus
  16. M. Vanhoucke, “Setup times and fast tracking in resource-constrained project scheduling,” Computers and Industrial Engineering, vol. 54, no. 4, pp. 1062–1070, 2008. View at Publisher · View at Google Scholar · View at Scopus
  17. C. Xu, A. Li, and X. Li, “Multi-project scheduling algorithm based on resource push-pull technology,” Computer Integrated Manufacturing Systems, vol. 16, no. 6, pp. 1246–1254, 2010. View at Google Scholar · View at Scopus
  18. D. Krüger and A. Scholl, “A heuristic solution framework for the resource constrained (multi-)project scheduling problem with sequence-dependent transfer times,” European Journal of Operational Research, vol. 197, no. 2, pp. 492–508, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  19. R. Kolisch, “Efficient priority rules for the resource-constrained project scheduling problem,” Journal of Operations Management, vol. 14, no. 3, pp. 179–192, 1996. View at Publisher · View at Google Scholar · View at Scopus
  20. V. Valls, S. Quintanilla, and F. Ballestín, “Resource-constrained project scheduling: a critical activity reordering heuristic,” European Journal of Operational Research, vol. 149, no. 2, pp. 282–301, 2003. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  21. J. Mendes, J. Gonçalves, and M. Resende, “A random key based genetic algorithm for the resource constrained project scheduling problem,” Computers and Operations Research, vol. 36, no. 1, pp. 92–109, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  22. N. Pan, P. Hsaio, and K. Chen, “A study of project scheduling optimization using Tabu Search algorithm,” Engineering Applications of Artificial Intelligence, vol. 21, no. 7, pp. 1101–1112, 2008. View at Publisher · View at Google Scholar · View at Scopus
  23. D. S. Yamashita, V. A. Armentano, and M. Laguna, “Scatter search for project scheduling with resource availability cost,” European Journal of Operational Research, vol. 169, no. 2, pp. 623–637, 2006. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  24. A. Lova, P. Tormos, M. Cervantes, and F. Barber, “An efficient hybrid genetic algorithm for scheduling projects with resource constraints and multiple execution modes,” International Journal of Production Economics, vol. 117, no. 2, pp. 302–316, 2009. View at Publisher · View at Google Scholar · View at Scopus
  25. K. W. Kim, Y. S. Yun, J. M. Yoon, M. Gen, and G. Yamazaki, “Hybrid genetic algorithm with adaptive abilities for resource-constrained multiple project scheduling,” Computers in Industry, vol. 56, no. 2, pp. 143–160, 2005. View at Publisher · View at Google Scholar · View at Scopus
  26. W. Chen, Y. Shi, H. Teng, X. Lan, and L. Hu, “An efficient hybrid algorithm for resource-constrained project scheduling,” Information Sciences, vol. 180, no. 6, pp. 1031–1039, 2010. View at Publisher · View at Google Scholar · View at Scopus
  27. M. Ranjbar, “Solving the resource-constrained project scheduling problem using filter-and-fan approach,” Applied Mathematics and Computation, vol. 201, no. 1-2, pp. 313–318, 2008. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  28. L. Deng, Y. Lin, and M. Chen, “Hybrid ant colony optimization for the resource-constrained project scheduling problem,” Journal of Systems Engineering and Electronics, vol. 21, no. 1, pp. 67–71, 2010. View at Publisher · View at Google Scholar · View at Scopus
  29. Z. Huang, “Quantum-inspired evolutionary algorithm for resources constrainted project scheduling problem,” Computer Integrated Manufacturing Systems, vol. 15, no. 9, pp. 1779–1822, 2009. View at Google Scholar · View at Scopus
  30. V. V. Peteghem and M. Vanhoucke, “A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem,” European Journal of Operational Research, vol. 201, no. 2, pp. 409–418, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  31. Y. Ying, Y. Shou, and M. Li, “Hybrid genetic algorithm for resource constrained multi-project scheduling problem,” Journal of Zhejiang University, vol. 43, no. 1, pp. 23–27, 2009. View at Publisher · View at Google Scholar · View at Scopus
  32. J. Montoya-Torres, E. Gutierrez-Franco, and C. Pirachicán-Mayorga, “Project scheduling with limited resources using a genetic algorithm,” International Journal of Project Management, vol. 28, no. 6, pp. 619–628, 2010. View at Publisher · View at Google Scholar · View at Scopus
  33. V. Valls, F. Ballestín, and S. Quintanilla, “A hybrid genetic algorithm for the resource-constrained project scheduling problem,” European Journal of Operational Research, vol. 185, no. 2, pp. 495–508, 2008. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  34. K. Bouleimen and H. Lecocq, “A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version,” European Journal of Operational Research, vol. 149, no. 2, pp. 268–281, 2003. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  35. S. Elloumi and P. Fortemps, “A hybrid rank-based evolutionary algorithm applied to multi-mode resource-constrained project scheduling problem,” European Journal of Operational Research, vol. 205, no. 1, pp. 31–41, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  36. M. Al-Fawzan and M. Haouari, “A bi-objective model for robust resource-constrained project scheduling,” International Journal of Production Economics, vol. 96, no. 2, pp. 175–187, 2005. View at Publisher · View at Google Scholar · View at Scopus
  37. S. Hartmann and D. Briskorn, “A survey of variants and extensions of the resource-constrained project scheduling problem,” European Journal of Operational Research, vol. 207, no. 1, pp. 1–14, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  38. C. Fang and L. Wang, “Survey on resource-constrained project scheduling,” Control and Decision, vol. 25, no. 5, pp. 641–656, 2010. View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  39. R. Kolisch and R. Padman, “An integrated survey of deterministic project scheduling,” Omega, vol. 29, no. 3, pp. 249–272, 2001. View at Publisher · View at Google Scholar · View at Scopus
  40. F. Ballestín and R. Blanco, “Theoretical and practical fundamentals for multi-objective optimisation in resource-constrained project scheduling problems,” Computers and Operations Research, vol. 38, no. 1, pp. 51–62, 2011. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  41. W. Herroelen and R. Leus, “Project scheduling under uncertainty: survey and research potentials,” European Journal of Operational Research, vol. 165, no. 2, pp. 289–306, 2005. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  42. J. Wglarz, J. Józefowska, M. Mika, and G. Waligóra, “Project scheduling with finite or infinite number of activity processing modes-a survey,” European Journal of Operational Research, vol. 208, no. 3, pp. 177–205, 2011. View at Publisher · View at Google Scholar · View at Scopus
  43. J. Buddhakulsomsiri and D. S. Kim, “Properties of multi-mode resource-constrained project scheduling problems with resource vacations and activity splitting,” European Journal of Operational Research, vol. 175, no. 1, pp. 279–295, 2006. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  44. J. Buddhakulsomsiri and D. S. Kim, “Priority rule-based heuristic for multi-mode resource-constrained project scheduling problems with resource vacations and activity splitting,” European Journal of Operational Research, vol. 178, no. 2, pp. 374–390, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  45. L. Deng and Y. Lin, “Particle swarm optimization for resource-constrained project scheduling problems with activity splitting,” Control and Decision, vol. 23, no. 6, pp. 681–688, 2008. View at Google Scholar · View at Scopus
  46. X. Luo, D. Wang, and J. Tang, “Project scheduling problem involving time-splittable tasks,” Journal of Northeastern University, vol. 27, no. 9, pp. 961–964, 2006. View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  47. M. Eusuff and K. Lansey, “Optimization of water distribution network design using the shuffled frog leaping algorithm,” Journal of Water Resources Planning and Management, vol. 129, no. 3, pp. 210–225, 2003. View at Publisher · View at Google Scholar · View at Scopus
  48. M. Eusuff, K. Lansey, and F. Pasha, “Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization,” Engineering Optimization, vol. 38, no. 2, pp. 129–154, 2006. View at Publisher · View at Google Scholar · View at Scopus
  49. A. Rahimi-Vahed, M. Dangchi, H. Rafiei, and E. Salimi, “A novel hybrid multi-objective shuffled frog-leaping algorithm for a bi-criteria permutation flow shop scheduling problem,” International Journal of Advanced Manufacturing Technology, vol. 41, no. 11-12, pp. 1227–1239, 2009. View at Publisher · View at Google Scholar · View at Scopus
  50. A. Rahimi-Vahed and A. H. Mirzaei, “A hybrid multi-objective shuffled frog-leaping algorithm for a mixed-model assembly line sequencing problem,” Computers and Industrial Engineering, vol. 53, no. 4, pp. 642–666, 2007. View at Publisher · View at Google Scholar · View at Scopus
  51. B. Amiri, M. Fathian, and A. Maroosi, “Application of shuffled frog-leaping algorithm on clustering,” International Journal of Advanced Manufacturing Technology, vol. 45, no. 1-2, pp. 199–209, 2009. View at Publisher · View at Google Scholar · View at Scopus
  52. H. Elbehairy, E. Elbeltagi, T. Hegazy, and K. Soudki, “Comparison of two evolutionary algorithms for optimization of bridge deck repairs,” Computer-Aided Civil and Infrastructure Engineering, vol. 21, no. 8, pp. 561–572, 2006. View at Publisher · View at Google Scholar · View at Scopus
  53. E. Elbeltagi, T. Hegazy, and D. Grierson, “Comparison among five evolutionary-based optimization algorithms,” Advanced Engineering Informatics, vol. 19, no. 1, pp. 43–53, 2005. View at Publisher · View at Google Scholar · View at Scopus
  54. N. Wang, X. Li, and X. Chen, “Fast three-dimensional Otsu thresholding with shuffled frog-leaping algorithm,” Pattern Recognition Letters, vol. 31, no. 13, pp. 1809–1815, 2010. View at Publisher · View at Google Scholar · View at Scopus