较新颖的智能优化算法

news/2024/7/3 0:02:05

较新颖的智能优化算法

序号方法参考文献年份
1人群搜索算法Dai, C., Y. Zhu, and W. Chen. Seeker optimization algorithm. in International Conference on Computational and Information Science. 2006. Springer.2006
2人工蜂群算法Karaboga, D. and B.J.J.o.g.o. Basturk, A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. 2007. 39(3): p. 459-471.2007
3帝国竞争算法Atashpaz-Gargari, E. and C. Lucas. Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition. in 2007 IEEE congress on evolutionary computation. 2007. Ieee.2007
4智能水滴算法Hosseini, H.S. Problem solving by intelligent water drops. in 2007 IEEE congress on evolutionary computation. 2007. IEEE.2007
5生物地理优化算法Simon, D.J.I.t.o.e.c., Biogeography-based optimization. 2008. 12(6): p. 702-713.2008
6萤火虫算法Yang, X.-S. Firefly algorithms for multimodal optimization. in International symposium on stochastic algorithms. 2009. Springer.2009
7布谷鸟搜索算法Yang, X.-S. and S. Deb. Cuckoo search via Lévy flights. in 2009 World congress on nature & biologically inspired computing (NaBIC). 2009. IEEE.2009
8引力搜索算法Rashedi, E., H. Nezamabadi-Pour, and S.J.I.s. Saryazdi, GSA: a gravitational search algorithm. 2009. 179(13): p. 2232-2248.2009
9觅食搜索算法Oftadeh, R., et al., A novel meta-heuristic optimization algorithm inspired by group hunting of animals: Hunting search. 2010. 60(7): p. 2087-2098.2010
10蝙蝠算法Yang, X.-S., A new metaheuristic bat-inspired algorithm, in Nature inspired cooperative strategies for optimization (NICSO 2010). 2010, Springer. p. 65-74.2010
11风驱动优化算法Bayraktar, Z., M. Komurcu, and D.H. Werner. Wind Driven Optimization (WDO): A novel nature-inspired optimization algorithm and its application to electromagnetics. in 2010 IEEE antennas and propagation society international symposium. 2010. IEEE.2010
12手榴弹爆炸算法Ahrari, A. and A.A.J.A.S.C. Atai, Grenade explosion method—a novel tool for optimization of multimodal functions. 2010. 10(4): p. 1132-1140.2010
13头脑风暴优化算法Shi, Y. Brain storm optimization algorithm. in International conference in swarm intelligence. 2011. Springer.2011
14基于教与学的优化算法Rao, R.V., V.J. Savsani, and D.J.C.-A.D. Vakharia, Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. 2011. 43(3): p. 303-315.2011
15花授粉算法Yang, X.-S. Flower pollination algorithm for global optimization. in International conference on unconventional computing and natural computation. 2012. Springer.2012
16果蝇优化算法Pan, W.-T.J.K.-B.S., A new fruit fly optimization algorithm: taking the financial distress model as an example. 2012. 26: p. 69-74.2012
17磷虾优化算法Gandomi, A.H., A.H.J.C.i.n.s. Alavi, and n. simulation, Krill herd: a new bio-inspired optimization algorithm. 2012. 17(12): p. 4831-4845.2012
18狼群算法吴虎胜, 张凤鸣, and 吴.J. 系统工程与电子技术, 一种新的群体智能算法——狼群算法. 2010. 35(11): p. 2430-2438.2010
19海豚回声定位算法Kaveh, A. and N.J.A.i.E.S. Farhoudi, A new optimization method: Dolphin echolocation. 2013. 59: p. 53-70.2013
20鸽群优化算法Duan, H., P.J.I.j.o.i.c. Qiao, and cybernetics, Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning. 2014.2014
21灰狼优化算法Mirjalili, S., S.M. Mirjalili, and A.J.A.i.e.s. Lewis, Grey wolf optimizer. 2014. 69: p. 46-61.2014
22物体碰撞优化算法Kaveh, A., V.R.J.C. Mahdavi, and Structures, Colliding bodies optimization: a novel meta-heuristic method. 2014. 139: p. 18-27.2014
23水波优化 算法Zheng, Y.-J.J.C. and O. Research, Water wave optimization: a new nature-inspired metaheuristic. 2015. 55: p. 1-11.2015
24闪电搜索算法Shareef, H., A.A. Ibrahim, and A.H.J.A.S.C. Mutlag, Lightning search algorithm. 2015. 36: p. 315-333.2015
25Jaya算法Rao, R.J.I.J.o.I.E.C., Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems. 2016. 7(1): p. 19-34.2016
26蜻蜓算法Mirjalili, S.J.N.C. and Applications, Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. 2016. 27(4): p. 1053-1073.2016
27鲸鱼优化算法Mirjalili, S. and A.J.A.i.e.s. Lewis, The whale optimization algorithm. 2016. 95: p. 51-67.2016
28多元宇宙优化算法Mirjalili, S., et al., Multi-verse optimizer: a nature-inspired algorithm for global optimization. 2016. 27(2): p. 495-513.2016
29乌鸦搜索算法Askarzadeh, A.J.C. and Structures, A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm. 2016. 169: p. 1-12.2016
30蝴蝶算法Qi, X., Y. Zhu, and H.J.J.o.c.s. Zhang, A new meta-heuristic butterfly-inspired algorithm. 2017. 23: p. 226-239.2017
31雷电附着优化算法Nematollahi, A.F., A. Rahiminejad, and B.J.A.S.C. Vahidi, A novel physical based meta-heuristic optimization method known as Lightning Attachment Procedure Optimization. 2017. 59: p. 596-621.2017
32斑鬣狗优化算法Dhiman, G. and V.J.A.i.E.S. Kumar, Spotted hyena optimizer: a novel bio-inspired based metaheuristic technique for engineering applications. 2017. 114: p. 48-70.2017
33松鼠搜索算法Jain, M., et al., A novel nature-inspired algorithm for optimization: Squirrel search algorithm. 2019. 44: p. 148-175.2019

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