About this Journal Submit a Manuscript Table of Contents
Journal of Applied Mathematics
Volume 2013 (2013), Article ID 742653, 8 pages
http://dx.doi.org/10.1155/2013/742653
Research Article

A Hybrid Metaheuristic for Multiple Runways Aircraft Landing Problem Based on Bat Algorithm

1College of Information Science and Engineering, Guangxi University for Nationalities, Nanning, Guangxi 530006, China
2Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis, Nanning, Guangxi 530006, China

Received 17 May 2013; Accepted 11 July 2013

Academic Editor: Xin-She Yang

Copyright © 2013 Jian Xie 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. E. Beasley, M. Krishnamoorthy, Y. M. Sharaiha, and D. Abramson, “Scheduling aircraft landings—the static case,” Transportation Science, vol. 34, no. 2, pp. 180–197, 2000. View at Scopus
  2. H. Pinol and J. E. Beasley, “Scatter search and bionomic algorithms for the aircraft landing problem,” European Journal of Operational Research, vol. 171, no. 2, pp. 439–462, 2006. View at Publisher · View at Google Scholar · View at Scopus
  3. J. A. Bennell, M. Mesgarpour, and C. N. Potts, “Airport runway scheduling,” Annals of Operations Research, vol. 204, pp. 249–270, 2013. View at Publisher · View at Google Scholar
  4. A. R. Brentnall and R. C. H. Cheng, “Some effects of aircraft arrival sequence algorithms,” Journal of the Operational Research Society, vol. 60, no. 7, pp. 962–972, 2009. View at Publisher · View at Google Scholar · View at Scopus
  5. M. Wen, Algorithms of Scheduling Aircraft Landing Problem, Technical University of Denmark, DTU, Lyngby, Denmark, 2005.
  6. N. Bäuerle, O. Engelhardt-Funke, and M. Kolonko, “On the waiting time of arriving aircrafts and the capacity of airports with one or two runways,” European Journal of Operational Research, vol. 177, no. 2, pp. 1180–1196, 2006. View at Publisher · View at Google Scholar · View at Scopus
  7. X.-B. Hu and E. Di Paolo, “An efficient genetic algorithm with uniform crossover for air traffic control,” Computers and Operations Research, vol. 36, no. 1, pp. 245–259, 2009. View at Publisher · View at Google Scholar · View at Scopus
  8. G. Bencheikh, J. Boukachour, and A. E. H. Alaoui, “Improved ant colony algorithm to solve the aircraft landing problem,” International Journal of Computer Theory and Engineering, vol. 3, no. 2, pp. 224–233, 2011.
  9. A. Salehipour, M. Modarres, and N. L. Moslemi, “An efficient hybrid meta-heuristic for aircraft landing problem,” Computers & Operations Research, vol. 40, no. 1, pp. 207–213, 2013.
  10. S.-P. Yu, X.-B. Cao, and J. Zhang, “A real-time schedule method for aircraft landing scheduling problem based on cellular automation,” Applied Soft Computing Journal, vol. 11, no. 4, pp. 3485–3493, 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. G. Hancerliogullari, G. Rabadi, A. H. Al-Salem, and M. Kharbeche, “Greedy algorithms and metaheuristics for a multiple runway combined arrival-departure aircraft sequencing problem,” Journal of Air Transport Management, vol. 32, pp. 39–48, 2013. View at Publisher · View at Google Scholar
  12. D. Briskorn and R. Stolletz, “Aircraft landing problems with aircraft classes,” Journal of Scheduling, pp. 1–15, 2013. View at Publisher · View at Google Scholar
  13. X. S. Yang, “A new metaheuristic bat-inspired algorithm,” in Nature Inspired Cooperative Strategies for Optimization (NICSO '10), pp. 65–74, Springer, Berlin, Germany, 2010.
  14. A. H. Gandomi, X. S. Yang, A. H. Alavi, and S. Talatahari, “Bat algorithm for constrained optimization tasks,” Neural Computing and Applications, vol. 22, no. 6, pp. 1239–1255, 2013. View at Publisher · View at Google Scholar
  15. X. S. Yang and A. H. Gandomi, “Bat algorithm: a novel approach for global engineering optimization,” Engineering Computations, vol. 29, no. 5, pp. 464–483, 2012.
  16. S. Mishra, K. Shaw, and D. Mishra, “A new meta-heuristic bat inspired classification approach for microarray data,” Procedia Technology, vol. 4, pp. 802–806, 2012.
  17. J. Xie, Y. Zhou, and H. Chen, “A novel bat algorithm based on differential operator and Lévy-flights trajectory,” Computational Intelligence and Neuroscience, vol. 2013, Article ID 453812, 13 pages, 2013. View at Publisher · View at Google Scholar
  18. G. Wang, L. Guo, H. Duan, L. Liu, and H. Wang, “A bat algorithm with mutation for UCAV path planning,” The Scientific World Journal, vol. 2012, Article ID 418946, 15 pages, 2012. View at Publisher · View at Google Scholar