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较新颖的智能优化算法[通俗易懂]
发布时间:2024-08-12 02:10浏览次数:

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

25

Jaya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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