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Mathematical Problems in Engineering
Volume 2017, Article ID 9843735, 12 pages
https://doi.org/10.1155/2017/9843735
Research Article

Research on Multiaircraft Cooperative Suppression Interference Array Based on an Improved Multiobjective Particle Swarm Optimization Algorithm

1Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xian 710038, China
2Tianjin University, Tianjin 300072, China

Correspondence should be addressed to Huan Zhang; nc.ude.ujt@4111ycs

Received 26 October 2016; Revised 11 January 2017; Accepted 17 January 2017; Published 5 March 2017

Academic Editor: Thomas Hanne

Copyright © 2017 Huan Zhang 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. G. L. Fan, Z. M. Yang, and Y. Z. Wang, “Evaluation of four countering efficiency of netted radar based on multi-stage fuzzy synthetic judgment,” Shipboard Electronic Countermeasure, vol. 36, no. 3, pp. 100–102, 2013. View at Google Scholar
  2. X. X. Zhang, “‘Four countering’ of radar in the early of the 21st century,” Radar Science and Technology, vol. 1, no. 1, pp. 1–6, 2013. View at Google Scholar
  3. H. S. Shi, D. Li, Z. G. Zhao, S. Mao, and C. Shi, “Electronic jamming exercises influence on flight path planning of low observation aircraft,” Journal of Nanjing University of Aeronautics and Astronautics, vol. 39, no. 2, pp. 154–158, 2007. View at Google Scholar · View at Scopus
  4. Z.-J. Wang, X. Li, Q.-M. Zhou, and W.-L. Wang, “Optimal deployment of radar network based on multi-constrained GA,” Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, vol. 30, no. 2, pp. 265–268, 2008. View at Google Scholar · View at Scopus
  5. S. J. Zhang, “Combat efficiency calculating method of long distance airborne jamming aircraft against ground early warning radar,” Technology of Electronic Countermeasure, vol. 19, no. 3, pp. 29–31, 2004. View at Google Scholar
  6. M. Z. Ruan, H. J. Wang, Q. M. Li et al., “Efficiency evaluation of multi-jamming sources on stand-off jamming based on the exposed range,” Systems Engineering and Electronics, vol. 31, no. 9, pp. 2110–2114, 2009. View at Google Scholar
  7. Z. Tang, X.-G. Gao, and Y. Zhang, “Research on the model evaluating the efficiency of the airborne active self-defense jamming system,” Systems Engineering and Electronics, vol. 30, no. 2, pp. 236–239, 2008. View at Google Scholar · View at Scopus
  8. Z.-Q. Chen, L. Yu, Y. Lu, and Z.-L. Zhou, “Research on optimized electronic warfare embattling countermining radar net,” Acta Armamentarii, vol. 33, no. 1, pp. 89–94, 2012. View at Google Scholar · View at Scopus
  9. C. A. Coello Coello, G. T. Pulido, and M. S. Lechuga, “Handling multiple objectives with particle swarm optimization,” IEEE Transactions on Evolutionary Computation, vol. 8, no. 3, pp. 256–279, 2004. View at Publisher · View at Google Scholar · View at Scopus
  10. W. Hu, G. G. Yen, and X. Zhang, “Multiobjective particle swarm optimization based on Pareto entropy,” Journal of Software, vol. 25, no. 5, pp. 1025–1050, 2014. View at Publisher · View at Google Scholar · View at Scopus
  11. M. G. Gong, Q. Cai, X. W. Chen, and L. Ma, “Complex network clustering by multiobjective discrete particle swarm optimization based on decomposition,” IEEE Transactions on Evolutionary Computation, vol. 18, no. 1, pp. 82–97, 2014. View at Publisher · View at Google Scholar · View at Scopus
  12. M. G. Gong, L. C. Jiao, D. D. Yang, and W. P. Ma, “Research on evolutionary multi-objective optimization algorithms,” Journal of Software, vol. 20, no. 2, pp. 271–289, 2009. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  13. G.-H. Hu, Z.-Z. Mao, and D.-K. He, “Multi-objective optimization for leaching process using improved two-stage guide PSO algorithm,” Journal of Central South University of Technology, vol. 18, no. 4, pp. 1200–1210, 2011. View at Publisher · View at Google Scholar · View at Scopus
  14. R. S. MacIel, M. Rosa, V. Miranda, and A. Padilha-Feltrin, “Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation,” Electric Power Systems Research, vol. 89, pp. 100–108, 2012. View at Publisher · View at Google Scholar · View at Scopus
  15. Y.-Z. Luo and L.-N. Zhou, “Asteroid rendezvous mission design using multiobjective particle swarm optimization,” Mathematical Problems in Engineering, vol. 2014, Article ID 823659, 13 pages, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  16. H. Xu, Y. Wang, and X. Xu, “Multiobjective particle swarm optimization based on dimensional update,” International Journal on Artificial Intelligence Tools, vol. 22, no. 3, Article ID 1350015, 2013. View at Publisher · View at Google Scholar
  17. Y. Cooren, M. Clerc, and P. Siarry, “MO-TRIBES, an adaptive multiobjective particle swarm optimization algorithm,” Computational Optimization and Applications, vol. 49, no. 2, pp. 379–400, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  18. L. D. S. Coelho, F. A. Guerra, and J. V. Leite, “Multiobjective exponential particle swarm optimization approach applied to hysteresis parameters estimation,” IEEE Transactions on Magnetics, vol. 48, no. 2, pp. 283–286, 2012. View at Publisher · View at Google Scholar · View at Scopus
  19. Y. Zhang, D.-W. Gong, and Z. Ding, “A bare-bones multi-objective particle swarm optimization algorithm for environmental/economic dispatch,” Information Sciences, vol. 192, pp. 213–227, 2012. View at Publisher · View at Google Scholar · View at Scopus
  20. F. Jolai, R. Tavakkoli-Moghaddam, and M. Taghipour, “A multi-objective particle swarm optimisation algorithm for unequal sized dynamic facility layout problem with pickup/drop-off locations,” International Journal of Production Research, vol. 50, no. 15, pp. 4279–4293, 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. S. M. Abd-Elazim and E. S. Ali, “Synergy of particle swarm optimization and bacterial foraging for TCSC damping controller design,” WSEAS Transactions on Power Systems, vol. 8, no. 2, pp. 74–84, 2013. View at Google Scholar · View at Scopus
  22. D. F. Zhang, Digital image processing with MATLAB, China Machine Press, Beijing, China, 2012.
  23. D. Liu, K. C. Tan, C. K. Goh, and W. K. Ho, “A multiobjective memetic algorithm based on particle swarm optimization,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 37, no. 1, pp. 42–50, 2007. View at Publisher · View at Google Scholar · View at Scopus
  24. J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proceedings of the IEEE International Conference on Neural Networks, pp. 1942–1948, December 1995. View at Scopus
  25. N. Al Moubayed, A. Petrovski, and J. McCall, “D2MOPSO: multi-objective particle swarm optimizer based on decomposition and dominance,” in Proceedings of the 12th Europe Conference on Evolutionary Computation Combinatorial Optimization, pp. 75–86, Málaga, Spain, April 2012.
  26. Z. Li, R. Ngambusabongsopa, and E. Mohammed, “A novel diversity guided particle swarm multi-objective optimization algorithm,” International Journal of Digital Content Technology and Its Applications, vol. 5, no. 1, pp. 269–278, 2011. View at Publisher · View at Google Scholar · View at Scopus
  27. C. A. Coello Coello and M. S. Lechuga, “MOPSO: a proposal for multiple objective particle swarm optimization,” in Proceedings of the Congress on Evolutionary Computation (CEC '02), pp. 1051–1056, IEEE, Honolulu, Hawaii, USA, May 2002. View at Publisher · View at Google Scholar · View at Scopus
  28. J. Hazra and A. K. Sinha, “A multi-objective optimal power flow using particle swarm optimization,” European Transactions on Electrical Power, vol. 21, no. 1, pp. 1028–1045, 2011. View at Publisher · View at Google Scholar · View at Scopus
  29. M. Daneshyari and G. G. Yen, “Cultural-based multiobjective particle swarm optimization,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 41, no. 2, pp. 553–567, 2011. View at Publisher · View at Google Scholar · View at Scopus
  30. X. Zhu, J. Zhang, and J. Feng, “Multiobjective particle swarm optimization based on PAM and uniform design,” Mathematical Problems in Engineering, vol. 2015, Article ID 126404, 17 pages, 2015. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  31. Q. F. Zhang and H. Li, “MOEA/D: a multiobjective evolutionary algorithm based on decomposition,” IEEE Transactions on Evolutionary Computation, vol. 11, no. 6, pp. 712–731, 2007. View at Publisher · View at Google Scholar · View at Scopus
  32. S.-J. Tsai, T.-Y. Sun, C.-C. Liu, S.-T. Hsieh, W.-C. Wu, and S.-Y. Chiu, “An improved multi-objective particle swarm optimizer for multi-objective problems,” Expert Systems with Applications, vol. 37, no. 8, pp. 5872–5886, 2010. View at Publisher · View at Google Scholar · View at Scopus