Table of metaheuristics

Add links
From Wikipedia, the free encyclopedia

This is a chronological table of metaheuristic algorithms that only contains fundamental algorithms. Hybrid algorithms and multi-objective algorithms are not listed in the table below.

Categories[edit]

  • Trajectory-based
  • Nature-inspired
    • Evolutionary-based
    • Swarm-based
    • Bio-inspired
    • Physics/Chemistry-based
    • Human-based
    • Plant-based
  • Art-inspired
  • Ancient-inspired

The table[edit]

Name Abbreviation Main category Subcategory Year published Ref.
Simulated Annealing SA Trajectory-based - 1983 [1]
Tabu Search TS Trajectory-based - 1989 [2]
Genetic Algorithm GA Evolutionary-based - 1992 [3]
Evolutionary Algorithm EA Evolutionary-based - 1994
Cultural Algorithm CA 1994 [4]
Particle Swarm Optimization PSO Nature-inspired Swarm-based 1995 [5]
Differential Evaluation DE Evolutionary-based - 1997 [6]
Local Search LS 1997
Variable neighborhood search VNS Trajectory-based - 1997 [7]
Guided Local Search GLS Trajectory-based - 1998 [8]
Clonal Selection Algorithm CSA Evolutionary-based - 2000 [9]
Harmony Search HS Evolutionary-based - 2001 [10]
Memetic Algorithm MA Evolutionary-based - 2002
Iterative Local Search ILS Trajectory-based - 2003 [11]
Artificial Bee Colony ABC Nature-inspired Bio-inspired 2005 [12]
Ant Colony Optimization ACO Nature-inspired Bio-inspired 2006 [13]
Glowworm Swarm Optimization GSO Nature-inspired Swarm-based 2006 [14]
Shuffled Frog Leaping Algorithm SFLA Nature-inspired Bio-inspired 2006 [15]
Invasive Weed Optimization IWO Nature-inspired Plant-based 2006 [16]
Seeker Optimization Algorithm SOA Nature-inspired Human-based 2006 [17]
Imperialistic Competitive Algorithm ICA Nature-inspired Human-based 2007 [18]
Central Force Optimization CFO 2007 [19]
Biogeography Based Optimization BBO Nature-inspired Human-based 2008 [20]
Firefly Algorithm FA Nature-inspired Bio-inspired 2008 [21]
Intelligent Water Drops IWD Nature-inspired Swarm-based 2008 [22]
Monkey Algorithm MA Nature-inspired Bio-inspired 2008 [23]
Cuckoo Search CS Nature-inspired Bio-inspired 2009 [24]
Group Search Optimizer GSO Nature-inspired Swarm-based 2009 [25]
Key Cutting Algorithm KCA 2009 [26]
Hunting Search HS Nature-inspired Swarm-based 2009 [27]
Chemical Reaction Optimization CRO Nature-inspired Physics/Chemistry-based 2009 [28]
Bat Algorithm BA Nature-inspired Bio-inspired 2010 [29]
Charged System Search CSS Nature-inspired Physics/Chemistry-based 2010 [30]
Eagle Strategy ES Nature-inspired 2010
Fireworks Algorithm FWA 2010 [31]
Cuckoo Optimization Algorithm COA Nature-inspired Bio-inspired 2011 [32]
Stochastic Diffusion Search SDS 2011
Teaching-Learning-Based Optimization TLBO Nature-inspired Human-based 2011 [33]
Bacterial Colony Optimization BCO 2012 [34]
Fruit Fly Optimization FFO 2012
Krill Herd Algorithm KHA Nature-inspired Bio-inspired 2012 [35]
Migrating Birds Optimization MBO Nature-inspired Swarm-based 2012 [36]
Water Cycle Algorithm WCA 2012
Backtracking Search Algorithm BSA Evolutionary-based - 2013 [37]
Black Hole Algorithm BH Nature-inspired Physics/Chemistry-based 2013 [38]
Dolphin Echolocation DE Nature-inspired Bio-inspired 2013 [39]
Animal Migration Optimization AMO Nature-inspired Swarm-based 2013 [40]
Keshtel Algorithm KA Nature-inspired 2014 [41]
SDA Optimization Algorithm SDA Nature-inspired Bio-inspired 2014 [42]
Artificial Root Foraging Algorithm ARFA Nature-inspired Plant-based 2014 [43]
Bumble Bees Mating Optimization BBMO 2014
Chicken Swarm Optimization CSO Nature-inspired Bio-inspired 2014 [44]
Colliding Bodies Optimization CBO 2014 [45]
Coral Reefs Optimization Algorithm CROA 2014
Flower Pollination Algorithm FPA Nature-inspired Plant-based 2014 [46]
Radial Movement Optimization RMO Nature-inspired Swarm-based 2014 [47]
Spider Monkey Optimization SMO Nature-inspired Bio-inspired 2014 [48]
Soccer League Competition SLC Nature-inspired Human-based 2014 [49]
Artificial Algae Algorithm AAA 2015 [50]
Adaptive Dimensional Search ADS 2015
Alienated Ant Algorithm AAA 2015
Artificial Fish Swarm Algorithm AFSA Nature-inspired 2015
Bottlenose Dolphin Optimization BDO Nature-inspired 2015 [51]
Cricket Algorithm CA 2015 [52]
Elephant Search Algorithm ESA Nature-inspired Bio-inspired 2015 [53]
Grey Wolf Optimizer GWO Nature-inspired Bio-inspired 2015 [54]
Jaguar Algorithm JA Nature-inspired Bio-inspired 2015 [55]
Locust Swarm Algorithm LSA Nature-inspired Swarm-based 2015 [56]
Moth-Flame Optimization MFO Nature-inspired Bio-inspired 2015 [57]
Stochastic Fractal Search SFF Evolutionary-based - 2015 [58]
Vortex Search Algorithm VSA Nature-inspired Physics/Chemistry-based 2015 [59]
Water Wave Optimization WWA Nature-inspired Physics/Chemistry-based 2015 [60]
Ant Lion Optimizer ALO Nature-inspired Bio-inspired 2015 [61]
African Buffalo Optimization ABO Nature-inspired Swarm-based 2015 [62]
Lightning Search Algorithm LSA Nature-inspired Physics/Chemistry-based 2015 [63]
Across Neighborhood Search ANS Evolutionary-based - 2016 [64]
Crow Search Algorithm CSA Nature-inspired Bio-inspired 2016 [65]
Electromagnetic Field Optimization EFO Nature-inspired Physics/Chemistry-based 2016 [66]
Joint Operations Algorithm JOA Nature-inspired Swarm-based 2016 [67]
Lion Optimization Algorithm LOA Nature-inspired Bio-inspired 2016 [68]
Sine Cosine Algorithm SCA Nature-inspired Physics/Chemistry-based 2016 [69]
Virus Colony Search VCS Nature-inspired Bio-inspired 2016 [70]
Whale Optimization Algorithm WOA Nature-inspired Bio-inspired 2016 [71]
Red Deer Algorithm RDA Nature-inspired Bio-inspired 2016 [72]
Phototropic Optimization Algorithm POA Nature-inspired Plant-based 2018 [73]
Coyote Optimization Algorithm COA Nature-inspired Swarm-based 2018 [74]
Owl Search Algorithm OSA Nature-inspired Bio-inspired 2018 [75]
Squirrel Search Algorithm SSA Nature-inspired Bio-inspired 2018 [76]
Social Engineering Optimizer SEO Nature-inspired Human-based 2018 [77]
Emperor Penguin Optimizer EPO Nature-inspired Bio-inspired 2018 [78]
Socio Evolution and Learning Optimization SELO Nature-inspired Human-based 2018 [79]
Future Search Algorithm FSA Nature-inspired Human-based 2019 [80]
Emperor Penguins Colony EPC Nature-inspired Swarm-based 2019 [81]
Thermal Exchange Optimization TEO Nature-inspired Physics/Chemistry-based 2019 [82]
Harris Hawks Optimization HHO Nature-inspired Bio-inspired 2019 [83]
Political Optimizer PO Nature-inspired Human-based 2020 [84]
Heap-Based Optimizer HBO Nature-inspired Human-based 2020 [85]
Color Harmony Algorithm CHA Art-inspired Color-based 2020 [86]
Stochastic Paint Optimizer SPO Art-inspired Color-based 2020 [87]
Giza Pyramids Construction GPC Ancient-inspired - 2020 [88]
Mayfly Optimization Algorithm MOA Nature-inspired Bio-inspired 2020 [89]
Fire Hawk Optimizer FHO Nature-inspired Bio-inspired 2022 [90]
Flying Fox Optimization Algorithm FFO Nature-inspired Bio-inspired 2023 [91]

References[edit]

  1. ^ Kirkpatrick, S.; Gelatt, C. D.; Vecchi, M. P. (1983-05-13). "Optimization by Simulated Annealing". Science. 220 (4598): 671–680. Bibcode:1983Sci...220..671K. doi:10.1126/science.220.4598.671. ISSN 0036-8075. PMID 17813860. S2CID 205939.
  2. ^ Glover, Fred (1989-08-01). "Tabu Search—Part I". ORSA Journal on Computing. 1 (3): 190–206. doi:10.1287/ijoc.1.3.190. ISSN 0899-1499.
  3. ^ Holland, John H. (1992). Adaptation in natural and artificial systems : an introductory analysis with applications to biology, control, and artificial intelligence (1st MIT Press ed.). Cambridge, Mass.: MIT Press. ISBN 0-585-03844-9. OCLC 42854623.
  4. ^ Sebald, Anthony V.; Fogel, Lawrence J. (1994-09-01). "Evolutionary Programming". Proceedings of the Third Annual Conference. WORLD SCIENTIFIC. pp. 1–386. doi:10.1142/9789814534116. ISBN 978-981-02-1810-2.
  5. ^ Kennedy, J.; Eberhart, R. (November 1995). "Particle swarm optimization". Proceedings of ICNN'95 - International Conference on Neural Networks. Vol. 4. pp. 1942–1948 vol.4. doi:10.1109/ICNN.1995.488968. ISBN 0-7803-2768-3. S2CID 7367791.
  6. ^ Storn, Rainer; Price, Kenneth (1997-12-01). "Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces". Journal of Global Optimization. 11 (4): 341–359. Bibcode:1997JGOpt..11..341S. doi:10.1023/A:1008202821328. ISSN 1573-2916. S2CID 5297867.
  7. ^ Mladenović, N.; Hansen, P. (1997-11-01). "Variable neighborhood search". Computers & Operations Research. 24 (11): 1097–1100. doi:10.1016/S0305-0548(97)00031-2. ISSN 0305-0548.
  8. ^ Balas, Egon; Vazacopoulos, Alkis (1998-02-01). "Guided Local Search with Shifting Bottleneck for Job Shop Scheduling". Management Science. 44 (2): 262–275. doi:10.1287/mnsc.44.2.262. ISSN 0025-1909.
  9. ^ de Castro, L.N.; Von Zuben, F.J. (June 2002). "Learning and optimization using the clonal selection principle". IEEE Transactions on Evolutionary Computation. 6 (3): 239–251. doi:10.1109/TEVC.2002.1011539. ISSN 1941-0026.
  10. ^ Zong Woo Geem; Joong Hoon Kim; Loganathan, G.V. (February 2001). "A New Heuristic Optimization Algorithm: Harmony Search". Simulation. 76 (2): 60–68. doi:10.1177/003754970107600201. ISSN 0037-5497. S2CID 20076748.
  11. ^ Lourenço, Helena R.; Martin, Olivier C.; Stützle, Thomas (2003). "Iterated Local Search". In Glover, Fred; Kochenberger, Gary A. (eds.). Handbook of Metaheuristics. International Series in Operations Research & Management Science. Boston, MA: Springer US. pp. 320–353. doi:10.1007/0-306-48056-5_11. ISBN 978-0-306-48056-0. S2CID 198489826.
  12. ^ Karaboga, Dervis; Basturk, Bahriye (2007-11-01). "A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm". Journal of Global Optimization. 39 (3): 459–471. doi:10.1007/s10898-007-9149-x. ISSN 1573-2916. S2CID 8540283.
  13. ^ Dorigo, Marco; Birattari, Mauro; Stutzle, Thomas (November 2006). "Ant colony optimization". IEEE Computational Intelligence Magazine. 1 (4): 28–39. doi:10.1109/MCI.2006.329691. ISSN 1556-6048.
  14. ^ Krishnanand, K.N.; Ghose, D. (June 2005). "Detection of multiple source locations using a glowworm metaphor with applications to collective robotics". Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005. pp. 84–91. doi:10.1109/SIS.2005.1501606. ISBN 0-7803-8916-6. S2CID 17016908.
  15. ^ Eusuff, Muzaffar; Lansey, Kevin; Pasha, Fayzul (2006-03-01). "Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization". Engineering Optimization. 38 (2): 129–154. doi:10.1080/03052150500384759. ISSN 0305-215X. S2CID 18117277.
  16. ^ Mehrabian, A. R.; Lucas, C. (2006-12-01). "A novel numerical optimization algorithm inspired from weed colonization". Ecological Informatics. 1 (4): 355–366. Bibcode:2006EcInf...1..355M. doi:10.1016/j.ecoinf.2006.07.003. ISSN 1574-9541.
  17. ^ Dai, Chaohua; Zhu, Yunfang; Chen, Weirong (2007). "Seeker Optimization Algorithm". In Wang, Yuping; Cheung, Yiu-ming; Liu, Hailin (eds.). Computational Intelligence and Security. Lecture Notes in Computer Science. Vol. 4456. Berlin, Heidelberg: Springer. pp. 167–176. doi:10.1007/978-3-540-74377-4_18. ISBN 978-3-540-74377-4. S2CID 15135923.
  18. ^ Atashpaz-Gargari, Esmaeil; Lucas, Caro (September 2007). "Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition". 2007 IEEE Congress on Evolutionary Computation. pp. 4661–4667. doi:10.1109/CEC.2007.4425083. ISBN 978-1-4244-1339-3. S2CID 2736579.
  19. ^ Formato, Richard (2007). "Central Force Optimization: a New Metaheuristic with Applications in Applied Electromagnetics". Progress in Electromagnetics Research. 77: 425–491. doi:10.2528/PIER07082403. ISSN 1070-4698.
  20. ^ Simon, Dan (December 2008). "Biogeography-Based Optimization". IEEE Transactions on Evolutionary Computation. 12 (6): 702–713. doi:10.1109/TEVC.2008.919004. ISSN 1941-0026. S2CID 8319014.
  21. ^ Yang, Xin-She (2009). "Firefly Algorithms for Multimodal Optimization". In Watanabe, Osamu; Zeugmann, Thomas (eds.). Stochastic Algorithms: Foundations and Applications. Lecture Notes in Computer Science. Vol. 5792. Berlin, Heidelberg: Springer. pp. 169–178. doi:10.1007/978-3-642-04944-6_14. ISBN 978-3-642-04944-6. S2CID 34975975.
  22. ^ Hosseini, Hamed Shah (2009). "The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm". International Journal of Bio-Inspired Computation. 1 (1/2): 71. doi:10.1504/IJBIC.2009.022775. ISSN 1758-0366.
  23. ^ Zhao R Q, Tang W S. Monkey algorithm for global numerical optimization. Journal of Uncertain Systems. 2008,2 (3):164-175.
  24. ^ Yang, Xin-She; Suash Deb (December 2009). "Cuckoo Search via Lévy flights". 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC). pp. 210–214. doi:10.1109/NABIC.2009.5393690. ISBN 978-1-4244-5053-4. S2CID 206491725.
  25. ^ He, S.; Wu, Q. H.; Saunders, J. R. (October 2009). "Group Search Optimizer: An Optimization Algorithm Inspired by Animal Searching Behavior". IEEE Transactions on Evolutionary Computation. 13 (5): 973–990. doi:10.1109/TEVC.2009.2011992. ISSN 1941-0026. S2CID 38375639.
  26. ^ Qin, Jing (November 2009). "A new optimization algorithm and its application — Key cutting algorithm". 2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009). pp. 1537–1541. doi:10.1109/GSIS.2009.5408158. ISBN 978-1-4244-4914-9. S2CID 27652599.
  27. ^ Oftadeh, R.; Mahjoob, M. J.; Shariatpanahi, M. (2010-10-01). "A novel meta-heuristic optimization algorithm inspired by group hunting of animals: Hunting search". Computers & Mathematics with Applications. 60 (7): 2087–2098. doi:10.1016/j.camwa.2010.07.049. ISSN 0898-1221.
  28. ^ Lam, Albert Y. S.; Li, Victor O. K. (June 2010). "Chemical-Reaction-Inspired Metaheuristic for Optimization". IEEE Transactions on Evolutionary Computation. 14 (3): 381–399. doi:10.1109/TEVC.2009.2033580. hdl:10722/130634. ISSN 1941-0026. S2CID 2281747.
  29. ^ Yang, Xin-She (2010). "A New Metaheuristic Bat-Inspired Algorithm". In González, Juan R.; Pelta, David Alejandro; Cruz, Carlos; Terrazas, Germán (eds.). Nature Inspired Cooperative Strategies for Optimization (NICSO 2010). Studies in Computational Intelligence. Vol. 284. Berlin, Heidelberg: Springer. pp. 65–74. doi:10.1007/978-3-642-12538-6_6. ISBN 978-3-642-12538-6. S2CID 14494281.
  30. ^ Kaveh, A.; Talatahari, S. (2010-09-01). "A novel heuristic optimization method: charged system search". Acta Mechanica. 213 (3): 267–289. doi:10.1007/s00707-009-0270-4. ISSN 1619-6937. S2CID 119512430.
  31. ^ Tan, Ying; Zhu, Yuanchun (2010). "Fireworks Algorithm for Optimization". In Tan, Ying; Shi, Yuhui; Tan, Kay Chen (eds.). Advances in Swarm Intelligence. Lecture Notes in Computer Science. Vol. 6145. Berlin, Heidelberg: Springer Berlin Heidelberg. pp. 355–364. doi:10.1007/978-3-642-13495-1_44. ISBN 978-3-642-13494-4.
  32. ^ Rajabioun, Ramin (2011-12-01). "Cuckoo Optimization Algorithm". Applied Soft Computing. 11 (8): 5508–5518. doi:10.1016/j.asoc.2011.05.008. ISSN 1568-4946.
  33. ^ Rao, R. V.; Savsani, V. J.; Vakharia, D. P. (2011-03-01). "Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems". Computer-Aided Design. 43 (3): 303–315. doi:10.1016/j.cad.2010.12.015. ISSN 0010-4485.
  34. ^ Niu, Ben; Wang, Hong (2012-11-27). "Bacterial Colony Optimization". Discrete Dynamics in Nature and Society. 2012: 1–28. doi:10.1155/2012/698057.
  35. ^ Gandomi, Amir Hossein; Alavi, Amir Hossein (2012-12-01). "Krill herd: A new bio-inspired optimization algorithm". Communications in Nonlinear Science and Numerical Simulation. 17 (12): 4831–4845. Bibcode:2012CNSNS..17.4831G. doi:10.1016/j.cnsns.2012.05.010. ISSN 1007-5704.
  36. ^ Duman, Ekrem; Uysal, Mitat; Alkaya, Ali Fuat (2012-12-25). "Migrating Birds Optimization: A new metaheuristic approach and its performance on quadratic assignment problem". Information Sciences. 217: 65–77. doi:10.1016/j.ins.2012.06.032. ISSN 0020-0255.
  37. ^ Civicioglu, Pinar (2013-04-01). "Backtracking Search Optimization Algorithm for numerical optimization problems". Applied Mathematics and Computation. 219 (15): 8121–8144. doi:10.1016/j.amc.2013.02.017. ISSN 0096-3003.
  38. ^ Hatamlou, Abdolreza (2013-02-10). "Black hole: A new heuristic optimization approach for data clustering". Information Sciences. Including Special Section on New Trends in Ambient Intelligence and Bio-inspired Systems. 222: 175–184. doi:10.1016/j.ins.2012.08.023. ISSN 0020-0255.
  39. ^ Kaveh, A.; Farhoudi, N. (2013-05-01). "A new optimization method: Dolphin echolocation". Advances in Engineering Software. 59: 53–70. doi:10.1016/j.advengsoft.2013.03.004. ISSN 0965-9978.
  40. ^ Li, Xiangtao; Zhang, Jie; Yin, Minghao (2014-06-01). "Animal migration optimization: an optimization algorithm inspired by animal migration behavior". Neural Computing and Applications. 24 (7): 1867–1877. doi:10.1007/s00521-013-1433-8. ISSN 1433-3058. S2CID 4362350.
  41. ^ Chandra S S, Vinod (2014-03-01). "Solving the integrated scheduling of production and rail transportation problem by Keshtel algorithm". Applied Soft Computing. 25 (3): 184–203. doi:10.1016/j.asoc.2014.09.034. ISSN 1568-4946.
  42. ^ Chandra, Vinod (2014-03-01). "Smell Detection Agent Based Optimization Algorithm". J. Inst. Eng. India Ser. B. 97 (3): 431–436. doi:10.1007/s40031-014-0182-0.
  43. ^ Ma, Lianbo; Hu, Kunyuan; Zhu, Yunlong; Chen, Hanning; He, Maowei (2014). "A Novel Plant Root Foraging Algorithm for Image Segmentation Problems". Mathematical Problems in Engineering. 2014: 1–16. doi:10.1155/2014/471209. ISSN 1024-123X.
  44. ^ Meng, Xianbing; Liu, Yu; Gao, Xiaozhi; Zhang, Hengzhen (2014). "A New Bio-inspired Algorithm: Chicken Swarm Optimization". In Tan, Ying; Shi, Yuhui; Coello, Carlos A. Coello (eds.). Advances in Swarm Intelligence. Lecture Notes in Computer Science. Vol. 8794. Cham: Springer International Publishing. pp. 86–94. doi:10.1007/978-3-319-11857-4_10. ISBN 978-3-319-11857-4.
  45. ^ Kaveh, A.; Mahdavi, V. R. (2014-07-15). "Colliding bodies optimization: A novel meta-heuristic method". Computers & Structures. 139: 18–27. doi:10.1016/j.compstruc.2014.04.005. ISSN 0045-7949.
  46. ^ Yang, Xin-She (2012). "Flower Pollination Algorithm for Global Optimization". In Durand-Lose, Jérôme; Jonoska, Nataša (eds.). Unconventional Computation and Natural Computation. Lecture Notes in Computer Science. Vol. 7445. Berlin, Heidelberg: Springer Berlin Heidelberg. pp. 240–249. arXiv:1312.5673. doi:10.1007/978-3-642-32894-7_27. ISBN 978-3-642-32893-0. S2CID 8021636.
  47. ^ Rahmani, Rasoul; Yusof, Rubiyah (2014-12-01). "A new simple, fast and efficient algorithm for global optimization over continuous search-space problems: Radial Movement Optimization". Applied Mathematics and Computation. 248: 287–300. doi:10.1016/j.amc.2014.09.102. ISSN 0096-3003.
  48. ^ Bansal, Jagdish Chand; Sharma, Harish; Jadon, Shimpi Singh; Clerc, Maurice (2014-03-01). "Spider Monkey Optimization algorithm for numerical optimization". Memetic Computing. 6 (1): 31–47. doi:10.1007/s12293-013-0128-0. ISSN 1865-9292. S2CID 5714781.
  49. ^ Moosavian, Naser; Kasaee Roodsari, Babak (2014-08-01). "Soccer league competition algorithm: A novel meta-heuristic algorithm for optimal design of water distribution networks". Swarm and Evolutionary Computation. 17: 14–24. doi:10.1016/j.swevo.2014.02.002. ISSN 2210-6502.
  50. ^ Uymaz, Sait Ali; Tezel, Gulay; Yel, Esra (2015-06-01). "Artificial algae algorithm (AAA) for nonlinear global optimization". Applied Soft Computing. 31: 153–171. doi:10.1016/j.asoc.2015.03.003. ISSN 1568-4946.
  51. ^ Srivastava, Abhishek; Das, Dushmanta Kumar (2022-05-11). "A bottlenose dolphin optimizer: An application to solve dynamic emission economic dispatch problem in the microgrid". Knowledge-Based Systems. 243: 108455. doi:10.1016/j.knosys.2022.108455. ISSN 0950-7051. S2CID 247077277.
  52. ^ Canayaz, Murat; Karci, Ali (2016-03-01). "Cricket behaviour-based evolutionary computation technique in solving engineering optimization problems". Applied Intelligence. 44 (2): 362–376. doi:10.1007/s10489-015-0706-6. ISSN 1573-7497. S2CID 16194679.
  53. ^ Deb, Suash; Fong, Simon; Tian, Zhonghuan (October 2015). "Elephant Search Algorithm for optimization problems". 2015 Tenth International Conference on Digital Information Management (ICDIM). pp. 249–255. doi:10.1109/ICDIM.2015.7381893. ISBN 978-1-4673-9152-8. S2CID 2460217.
  54. ^ Mirjalili, Seyedali; Mirjalili, Seyed Mohammad; Lewis, Andrew (2014-03-01). "Grey Wolf Optimizer". Advances in Engineering Software. 69: 46–61. doi:10.1016/j.advengsoft.2013.12.007. hdl:10072/66188. ISSN 0965-9978. S2CID 15532140.
  55. ^ Chen, Chin-Chi; Tsai, Yung-Che; Liu, I-I; Lai, Chia-Chun; Yeh, Yi-Ting; Kuo, Shu-Yu; Chou, Yao-Hsin (October 2015). "A Novel Metaheuristic: Jaguar Algorithm with Learning Behavior". 2015 IEEE International Conference on Systems, Man, and Cybernetics. pp. 1595–1600. doi:10.1109/SMC.2015.282. ISBN 978-1-4799-8697-2. S2CID 11932094.
  56. ^ Cuevas, Erik; González, Adrián; Zaldívar, Daniel; Cisneros, Marco Pérez (2015). "An optimisation algorithm based on the behaviour of locust swarms". International Journal of Bio-Inspired Computation. 7 (6): 402. doi:10.1504/ijbic.2015.073178. ISSN 1758-0366.
  57. ^ Mirjalili, Seyedali (2015-11-01). "Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm". Knowledge-Based Systems. 89: 228–249. doi:10.1016/j.knosys.2015.07.006. ISSN 0950-7051.
  58. ^ Salimi, Hamid (2015-02-01). "Stochastic Fractal Search: A powerful metaheuristic algorithm". Knowledge-Based Systems. 75: 1–18. doi:10.1016/j.knosys.2014.07.025. ISSN 0950-7051.
  59. ^ Doğan, Berat; Ölmez, Tamer (2015-02-01). "A new metaheuristic for numerical function optimization: Vortex Search algorithm". Information Sciences. 293: 125–145. doi:10.1016/j.ins.2014.08.053. ISSN 0020-0255. S2CID 8464197.
  60. ^ Zheng, Yu-Jun (2015-03-01). "Water wave optimization: A new nature-inspired metaheuristic". Computers & Operations Research. 55: 1–11. doi:10.1016/j.cor.2014.10.008. ISSN 0305-0548.
  61. ^ Mirjalili, Seyedali (2015-05-01). "The Ant Lion Optimizer". Advances in Engineering Software. 83: 80–98. doi:10.1016/j.advengsoft.2015.01.010. ISSN 0965-9978.
  62. ^ Odili, Julius Beneoluchi; Kahar, Mohd Nizam Mohmad; Anwar, Shahid (2015-01-01). "African Buffalo Optimization: A Swarm-Intelligence Technique". Procedia Computer Science. 2015 IEEE International Symposium on Robotics and Intelligent Sensors (IEEE IRIS2015). 76: 443–448. doi:10.1016/j.procs.2015.12.291. ISSN 1877-0509.
  63. ^ Shareef, Hussain; Ibrahim, Ahmad Asrul; Mutlag, Ammar Hussein (2015-11-01). "Lightning search algorithm". Applied Soft Computing. 36: 315–333. doi:10.1016/j.asoc.2015.07.028. ISSN 1568-4946.
  64. ^ Wu, Guohua (2016-02-01). "Across neighborhood search for numerical optimization". Information Sciences. Special issue on Discovery Science. 329: 597–618. arXiv:1401.3376. doi:10.1016/j.ins.2015.09.051. ISSN 0020-0255. S2CID 25844630.
  65. ^ Askarzadeh, Alireza (2016-06-01). "A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm". Computers & Structures. 169: 1–12. doi:10.1016/j.compstruc.2016.03.001. ISSN 0045-7949.
  66. ^ Abedinpourshotorban, Hosein; Mariyam Shamsuddin, Siti; Beheshti, Zahra; Jawawi, Dayang N. A. (2016-02-01). "Electromagnetic field optimization: A physics-inspired metaheuristic optimization algorithm". Swarm and Evolutionary Computation. 26: 8–22. doi:10.1016/j.swevo.2015.07.002. ISSN 2210-6502.
  67. ^ Sun, Gaoji; Zhao, Ruiqing; Lan, Yanfei (2016-01-01). "Joint operations algorithm for large-scale global optimization". Applied Soft Computing. 38: 1025–1039. doi:10.1016/j.asoc.2015.10.047. ISSN 1568-4946.
  68. ^ Yazdani, Maziar; Jolai, Fariborz (2016-01-01). "Lion Optimization Algorithm (LOA): A nature-inspired metaheuristic algorithm". Journal of Computational Design and Engineering. 3 (1): 24–36. doi:10.1016/j.jcde.2015.06.003.
  69. ^ Mirjalili, Seyedali (2016-03-15). "SCA: A Sine Cosine Algorithm for solving optimization problems". Knowledge-Based Systems. 96: 120–133. doi:10.1016/j.knosys.2015.12.022. ISSN 0950-7051.
  70. ^ Li, Mu Dong; Zhao, Hui; Weng, Xing Wei; Han, Tong (2016-02-01). "A novel nature-inspired algorithm for optimization: Virus colony search". Advances in Engineering Software. 92: 65–88. doi:10.1016/j.advengsoft.2015.11.004. ISSN 0965-9978.
  71. ^ Mirjalili, Seyedali; Lewis, Andrew (2016-05-01). "The Whale Optimization Algorithm". Advances in Engineering Software. 95: 51–67. doi:10.1016/j.advengsoft.2016.01.008. ISSN 0965-9978.
  72. ^ Fathollahi-Fard, Amir Mohammad; Hajiaghaei-Keshteli, Mostafa; Tavakkoli-Moghaddam, Reza (2020-03-10). "Red deer algorithm (RDA): a new nature-inspired meta-heuristic". Soft Computing. 24 (19): 14637–14665. doi:10.1007/s00500-020-04812-z. ISSN 1433-7479. S2CID 215906392.
  73. ^ Vinod, Chandra S S; Anand, Hareendran S (2021). "Phototropic algorithm for global optimisation problems". Applied Intelligence. 51 (8): 5965–5977. doi:10.1007/s10489-020-02105-4. S2CID 234211731.
  74. ^ Pierezan, Juliano; Dos Santos Coelho, Leandro (July 2018). "Coyote Optimization Algorithm: A New Metaheuristic for Global Optimization Problems". 2018 IEEE Congress on Evolutionary Computation (CEC). pp. 1–8. doi:10.1109/CEC.2018.8477769. ISBN 978-1-5090-6017-7. S2CID 52932771.
  75. ^ Jain, Mohit; Maurya, Shubham; Rani, Asha; Singh, Vijander (2018-03-22). Thampi, Sabu M.; El-Alfy, El-Sayed M.; Mitra, Sushmita; Trajkovic, Ljiljana (eds.). "Owl search algorithm: A novel nature-inspired heuristic paradigm for global optimization". Journal of Intelligent & Fuzzy Systems. 34 (3): 1573–1582. doi:10.3233/JIFS-169452.
  76. ^ Jain, Mohit; Singh, Vijander; Rani, Asha (2019-02-01). "A novel nature-inspired algorithm for optimization: Squirrel search algorithm". Swarm and Evolutionary Computation. 44: 148–175. doi:10.1016/j.swevo.2018.02.013. ISSN 2210-6502. S2CID 58952523.
  77. ^ Fathollahi-Fard, Amir Mohammad; Hajiaghaei-Keshteli, Mostafa; Tavakkoli-Moghaddam, Reza (2018-06-01). "The Social Engineering Optimizer (SEO)". Engineering Applications of Artificial Intelligence. 72: 267–293. doi:10.1016/j.engappai.2018.04.009. ISSN 0952-1976.
  78. ^ Dhiman, Gaurav; Kumar, Vijay (2018-06-15). "Emperor penguin optimizer: a bio-inspired algorithm for engineering problems". Knowledge-Based Systems. 159: 20–50. doi:10.1016/j.knosys.2018.06.001. S2CID 52965498.
  79. ^ Kumar, Meeta; Kulkarni, Anand J.; Satapathy, Suresh Chandra (2018-04-01). "Socio evolution & learning optimization algorithm: A socio-inspired optimization methodology". Future Generation Computer Systems. 81: 252–272. doi:10.1016/j.future.2017.10.052. ISSN 0167-739X.
  80. ^ Elsisi, M. (2019-03-01). "Future search algorithm for optimization". Evolutionary Intelligence. 12 (1): 21–31. doi:10.1007/s12065-018-0172-2. ISSN 1864-5917. S2CID 56702321.
  81. ^ Harifi, Sasan; Khalilian, Madjid; Mohammadzadeh, Javad; Ebrahimnejad, Sadoullah (2019-06-01). "Emperor Penguins Colony: a new metaheuristic algorithm for optimization". Evolutionary Intelligence. 12 (2): 211–226. doi:10.1007/s12065-019-00212-x. ISSN 1864-5917.
  82. ^ Kaveh, A.; Dadras, A. (2017-08-01). "A novel meta-heuristic optimization algorithm: Thermal exchange optimization". Advances in Engineering Software. 110: 69–84. doi:10.1016/j.advengsoft.2017.03.014. ISSN 0965-9978.
  83. ^ Heidari, Ali Asghar; Mirjalili, Seyedali; Faris, Hossam; Aljarah, Ibrahim; Mafarja, Majdi; Chen, Huiling (2019-08-01). "Harris hawks optimization: Algorithm and applications". Future Generation Computer Systems. 97: 849–872. doi:10.1016/j.future.2019.02.028. hdl:10072/384262. ISSN 0167-739X. S2CID 86457167.
  84. ^ Askari, Qamar; Younas, Irfan; Saeed, Mehreen (2020-05-11). "Political Optimizer: A novel socio-inspired meta-heuristic for global optimization". Knowledge-Based Systems. 195: 105709. doi:10.1016/j.knosys.2020.105709. ISSN 0950-7051. S2CID 215830598.
  85. ^ Askari, Qamar; Saeed, Mehreen; Younas, Irfan (2020-07-18). "Heap-based optimizer inspired by corporate rank hierarchy for global optimization". Expert Systems with Applications. 161: 113702. doi:10.1016/j.eswa.2020.113702. ISSN 0957-4174. S2CID 225042569.
  86. ^ Zaeimi, Mohammad; Ghoddosian, Ali (2020-08-01). "Color harmony algorithm: an art-inspired metaheuristic for mathematical function optimization". Soft Computing. 24 (16): 12027–12066. doi:10.1007/s00500-019-04646-4. ISSN 1433-7479. S2CID 209543050.
  87. ^ Kaveh, Ali; Talatahari, Siamak; Khodadadi, Nima (2020). "Stochastic Paint Optimizer: theory and application in civil engineering". Engineering with Computers. 38 (3): 1921–1952. doi:10.1007/s00366-020-01179-5. ISSN 0177-0667. S2CID 225121551.
  88. ^ Harifi, Sasan; Mohammadzadeh, Javad; Khalilian, Madjid; Ebrahimnejad, Sadoullah (2020-07-13). "Giza Pyramids Construction: an ancient-inspired metaheuristic algorithm for optimization". Evolutionary Intelligence. 14 (4): 1743–1761. doi:10.1007/s12065-020-00451-3. ISSN 1864-5917. S2CID 220512280.
  89. ^ Zervoudakis, Konstantinos; Tsafarakis, Stelios (2020). "A mayfly optimization algorithm". Computers & Industrial Engineering. 145: 106559. doi:10.1016/j.cie.2020.106559. S2CID 219783081.
  90. ^ Azizi, Mahdi; Talatahari, Siamak; Gandomi, Amir H. (2023-01-01). "Fire Hawk Optimizer: a novel metaheuristic algorithm". Artificial Intelligence Review. 56 (1): 287–363. doi:10.1007/s10462-022-10173-w. ISSN 1573-7462. S2CID 250057522.
  91. ^ Zervoudakis, Konstantinos; Tsafarakis, Stelios (2023). "A global optimizer inspired from the survival strategies of flying foxes". Engineering with Computers. 39 (2): 1583–1616. doi:10.1007/s00366-021-01554-w. S2CID 245636526.
Retrieved from "https://en.wikipedia.org/w/index.php?title=Table_of_metaheuristics&oldid=1222134381"