Cuckoo search: recent advances and applications
Cuckoo search (CS) is a relatively new algorithm, developed by Yang and Deb in 2009, and the same has been found to be efficient in solving global optimization problems. In this paper, we review the fundamental ideas of cuckoo search and the latest developments as well as its applications. We analyz...
Uloženo v:
| Vydáno v: | Neural computing & applications Ročník 24; číslo 1; s. 169 - 174 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
London
Springer London
01.01.2014
Springer |
| Témata: | |
| ISSN: | 0941-0643, 1433-3058 |
| On-line přístup: | Získat plný text |
| Tagy: |
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Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
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| Abstract | Cuckoo search (CS) is a relatively new algorithm, developed by Yang and Deb in 2009, and the same has been found to be efficient in solving global optimization problems. In this paper, we review the fundamental ideas of cuckoo search and the latest developments as well as its applications. We analyze the algorithm and gain insight into its search mechanisms and find out why it is efficient. We also discuss the essence of algorithms and its link to self-organizing systems, and finally, we propose some important topics for further research. |
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| AbstractList | Cuckoo search (CS) is a relatively new algorithm, developed by Yang and Deb in 2009, and the same has been found to be efficient in solving global optimization problems. In this paper, we review the fundamental ideas of cuckoo search and the latest developments as well as its applications. We analyze the algorithm and gain insight into its search mechanisms and find out why it is efficient. We also discuss the essence of algorithms and its link to self-organizing systems, and finally, we propose some important topics for further research. |
| Author | Yang, Xin-She Deb, Suash |
| Author_xml | – sequence: 1 givenname: Xin-She surname: Yang fullname: Yang, Xin-She organization: School of Science and Technology, Middlesex University – sequence: 2 givenname: Suash surname: Deb fullname: Deb, Suash email: suashdeb@gmail.com organization: Cambridge Institute of Technology |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28641276$$DView record in Pascal Francis |
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| Keywords | Cuckoo search Metaheuristic Swarm intelligence optimization Nature-inspired algorithm Convergence Artificial life Parasite Global optimum Optimization Self organization Biomimetics Heuristic method Swarm intelligence Artificial intelligence Metamodel Mathematical programming |
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| PublicationTitle | Neural computing & applications |
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Games innovations conference (ICE-GIC), pp 1–7 YangXSEngineering optimisation: an introduction with metaheuristic applications2010New YorkWiley10.1002/9780470640425 ChoudharyKPurohitGNA new testing approach using cuckoo search to achieve multi-objective genetic algorithmJ Comput201134117119 KellerEFOrganisms, machines, and thunderstorms: a history of self-organization, part two. Complexity, emergence, and stable attractorsHist Stud Nat Sci2009391131 Yildiz AR (2012) Cuckoo search algorithm for the selection of optimal machine parameters in milling operations. 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IEEE Publications, USA, pp 210–214 WaltonSHassanOMorganKBrownMRModified cuckoo search: a new gradient free optimization algorithmChaos Solitons Fractals201144971071810.1016/j.chaos.2011.06.004 PavlyukevichILévy flights, non-local search and simulated annealingJ Comput Phys20072261830184410.1016/j.jcp.2007.06.0081125.650092356396 SrivastavaPRChisMDebSYangXSAn efficient optimization algorithm for structural software testingInt J Artif Intell20129S126877 NoghrehabadiAGhalambazMVosoughAA hybrid power series—Cuckoo search optimization algorithm to electrostatic deflection of micro fixed-fixed actuatorsInt J Multidiscip Sci Eng2011242226 Tein LH, Ramli R (2010) Recent advancements of nurse scheduling models and a potential path. In: Proceedings of 6th IMT-GT conference on mathematics, statistics and its applications (ICMSA 2010), pp 395–409 RenZHWangJGaoYLThe global convergence analysis of particle swarm optimization algorithm based on Markov chainControl Theory Appl (in Chinese)20112844624661240.68207 BhargavaVFateenSEKBonilla-PetricioletACuckoo search: a new nature-inspired optimization method for phase equilibrium calculationsFluid Phase Equilib201333719120010.1016/j.fluid.2012.09.018 Yang XS, Deb S, Fong S (2011) Accelerated particle swarm optimization and support vector machine for business optimization and applications. In: Networked digital technologies 2011. Commun Comput Inf Sci 136:53–66 YangXSGandomiAHBat algorithm: a novel approach for global engineering optimizationEng Comput201229511810.1108/026444012112358341265.91100 Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks. 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