참고문헌
- Z. Y. Li, T. Huang, S. M. Chen, and R. F. Li, "Overview of constrained optimization evolutionary algorithms," Journal of Software, vol. 28, no. 6, pp. 1529-1546, 2017.
- D. H. Xia, Y. X. Li, W. Y. Gong, and G. L. He, "An adaptive differential evolution algorithm for constrained optimization problems," Acta Electronica Sinica, vol. 44, no. 10, pp. 2535-2542, 2016.
- H. C. Liu and Z. J. Wu, "Differential evolution algorithm using rotation-based learning," Acta Electronica Sinica, vol. 31, no. 10, pp. 2040-2046, 2015.
- H. Zhou. H. Zhao, M. Li, and Y Cai, "Multi-strategy adaptive symbiotic organisms search algorithm," Journal of Air Force Engineering University (Natural Science Edition), vol. 17, no. 4, pp. 101-106, 2016.
- A. K. Ojha and Y. R. Naidu, "Hybridizing particle swarm optimization with invasive weed optimization for solving nonlinear constrained optimization problems," in Proceedings of Fourth International Conference on Soft Computing for Problem Solving. New Delhi, India: Springer, 2015, pp. 599-610.
- W. Gong, Z. Cai, and D. Liang, "Adaptive ranking mutation operator based differential evolution for constrained optimization," IEEE Transactions on Cybernetics, vol. 45, no. 4, pp. 716-727, 2014. https://doi.org/10.1109/TCYB.2014.2334692
- W. Long, W. Z. Zhang, Y. F. Huang, and Y. X. Chen, "A hybrid cuckoo search algorithm with feasibilitybased rule for constrained structural optimization," Journal of Central South University, vol. 21, no. 8, pp. 3197-3204, 2014. https://doi.org/10.1007/s11771-014-2291-y
- D. Karaboga and B. Akay, "A modified artificial bee colony (ABC) algorithm for constrained optimization problems," Applied Soft Computing, vol. 11, no. 3, pp. 3021-3031, 2011. https://doi.org/10.1016/j.asoc.2010.12.001
- J. G. Zheng, X. Wang, and R. H. Liu, "Epsilon-differential evolution algorithm for constrained optimization problems," Journal of Software, vol. 23, no. 9, pp. 2374-2387, 2012. https://doi.org/10.3724/SP.J.1001.2012.04149
- X. J. Bi and L. Zhang, "Self-adaptive constrained optimization algorithm," Systems Engineering and Electronics, vol. 37, no. 8, pp. 1909-1915, 2015.
- C. G. Cui and X. F. Yang, "Interior penalty rule based evolutionary algorithm for constrained optimization," Journal of Software, vol. 26, no.7, pp. 1688-1699, 2015.
- Y. Liang, Z., Wan, and D. Fang, "An improved artificial bee colony algorithm for solving constrained optimization problems," International Journal of Machine Learning and Cybernetics, vol. 8, no. 3, pp. 739-754, 2017. https://doi.org/10.1007/s13042-015-0357-2
- Y. Wang and Z. Cai, "Combining multiobjective optimization with differential evolution to solve constrained optimization problems," IEEE Transactions on Evolutionary Computation, vol. 16, no. 1, pp. 117-134, 2012. https://doi.org/10.1109/TEVC.2010.2093582
-
T. Takahama and S. Sakai, "Efficient constrained optimization by the
$\epsilon$ constrained adaptive differential evolution," in Proceedings of IEEE Congress on Evolutionary Computation, Barcelona, Spain, 2010, pp. 1-8. - M. Y. Cheng and D. Prayogo, "Symbiotic organisms search: a new metaheuristic optimization algorithm," Computers & Structures, vol. 139, pp. 98-112, 2014. https://doi.org/10.1016/j.compstruc.2014.03.007
- T. P. Runarsson and X. Yao, "Stochastic ranking for constrained evolutionary optimization," IEEE Transactions on Evolutionary Computation, vol. 4, no. 3, pp. 284-294, 2000. https://doi.org/10.1109/4235.873238