SCIENCE CHINA Information Sciences, Volume 62 , Issue 7 : 070208(2019) https://doi.org/10.1007/s11432-018-9728-x

Comprehensive learning pigeon-inspired optimizationwith tabu list

More info
  • ReceivedAug 1, 2018
  • AcceptedNov 30, 2018
  • PublishedApr 24, 2019


There is no abstract available for this article.


This work was supported by National Natural Science Fundation for Distinguished Young Scholars of China (Grant No. 61525304), National Natural Science Foundation of China (Grant Nos. 61773120, 61873328), Hunan Postgraduate Research Innovation Project of China (Grant No. CX2018B022), and Foundation for the Author of National Excellent Doctoral Dissertation of China (Grant No. 2014-92).


[1] Eiben E, Schippers C. On evolutionary exploration and exploitation. Fundam Inf, 1998, 35: 35--50 DOI: doi:10.3233/FI-1998-35123403. Google Scholar

[2] Crepinsek M, Liu S H, Mernik M. Exploration and exploitation in evolutionary algorithms. ACM Comput Surv, 2013, 45: 1-33 CrossRef Google Scholar

[3] Duan H, Qiao P. Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning. Int Jnl Intel Comp Cyber, 2014, 7: 24-37 CrossRef Google Scholar

[4] Liang J J, Qin A K, Suganthan P N. Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Trans Evol Computat, 2006, 10: 281-295 CrossRef Google Scholar

[5] Li H, Duan H. Bloch quantum-behaved Pigeon-inspired optimization for continuous optimization problems. In: Proceedings of Guidance, Navigation and Control Conference. New York: IEEE, 2014. 2634--2638. Google Scholar

[6] Zhang B, Duan H. Predator-prey pigeon-inspired optimization for UAV three-dimensional path planning. In: Proceedings of International Conference in Swarm Intelligence. Berlin: Springer, 2014. 96--105. Google Scholar

[7] Zhang S, Duan H. Gaussian pigeon-inspired optimization approach to orbital spacecraft formation reconfiguration. Chin J Aeronautics, 2015, 28: 200-205 CrossRef Google Scholar

[8] Li C, Duan H. Target detection approach for UAVs via improved Pigeon-inspired Optimization and Edge Potential Function. Aerospace Sci Tech, 2014, 39: 352-360 CrossRef Google Scholar