References
Duan H, Qiao P. Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning. Int J Intell Comput Cyber, 2014, 7: 24–37
Qiu H X, Duan H B. Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design. Sci China Technol Sci, 2015, 58: 1915–1923
Lin Q, Liu S, Zhu Q, et al. Particle swarm optimization with a balanceable fitness estimation for manyobjective optimization problems. IEEE Trans Evol Comput, 2018, 22: 32–46
Deb K, Jain H. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach. Part I: solving problems with box constraints. IEEE Trans Evol Comput, 2014, 18: 577–601
Yang S, Li M, Liu X, et al. A grid-based evolutionary algorithm for many-objective optimization. IEEE Trans Evol Comput, 2013, 17: 721–736
Bader J, Zitzler E. HypE: an algorithm for fast hypervolume-based many-objective optimization. Evolary Comput, 2011, 19: 45–76
Zhang X, Tian Y, Jin Y. A knee point-driven evolutionary algorithm for many-objective optimization. IEEE Trans Evol Comput, 2015, 19: 761–776
Zhang Q F, Li H. MOEA/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans Evol Comput, 2007, 11: 712–731
Acknowledgements
This work was supported by National Natural Science Foundation of China (Grant Nos. 61806138, U1636220, 61663028, 61702040), Natural Science Foundation of Shanxi Province (Grant No. 201801D121127), Scientific and Technological Innovation Team of Shanxi Province (Grant No. 201805D131007), Ph.D. Research Startup Foundation of Taiyuan University of Science and Technology (Grant No. 20182002), and Beijing Natural Science Foundation (Grant No. 4174089).
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Rights and permissions
About this article
Cite this article
Cui, Z., Zhang, J., Wang, Y. et al. A pigeon-inspired optimization algorithm for many-objective optimization problems. Sci. China Inf. Sci. 62, 70212 (2019). https://doi.org/10.1007/s11432-018-9729-5
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11432-018-9729-5