2013
DOI: 10.1007/s00521-013-1367-1
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Cuckoo search: recent advances and applications

Abstract: Cuckoo search (CS) is a relatively new algorithm, developed by Yang and Deb in 2009, and CS is 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 resea… Show more

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Cited by 895 publications
(422 citation statements)
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“…At this point, by subjecting a standard road excitation with some pits and bumps [9] (as shown in Fig. 2), the gains for PID controller can be adjusted via simulation with the parameters in Table 3.…”
Section: Quarter Car Dynamic Modelmentioning
confidence: 99%
See 1 more Smart Citation
“…At this point, by subjecting a standard road excitation with some pits and bumps [9] (as shown in Fig. 2), the gains for PID controller can be adjusted via simulation with the parameters in Table 3.…”
Section: Quarter Car Dynamic Modelmentioning
confidence: 99%
“…In order to demonstrate the reliability and efficiency of the proposed CS-PID controller in the SAS, passive suspension is introduced as an intuitive comparative case. Also, the conventional PID controller is utilized for the same SAS system as another comparative case [9].…”
Section: Simulation and Analysismentioning
confidence: 99%
“…In fact, the cuckoos boosting their mimic power and the host birds boosting their identification power and these effort and fight are an incessant matter. Various types of algorithms in various applications have been proposed which are inspired by the cuckoo's life like [46][47][48][49][50] but our method is very similar to [29]. Details of our method will be explained in Section 3.…”
Section: Cuckoo's Lifementioning
confidence: 99%
“…CSA has a few parameters needed to be tuned, and the inexperienced user can easily interact with it. It has two crucial search capabilities, which are local search and global search controlled by a fraction probability or discovery rate, P a internal parameter and therefore converges to the global optimum for a multimodal optimization [43]. It uses Lévy flights motion with infinite mean and variance rather than standard random walks motion for global search.…”
Section: Introductionmentioning
confidence: 99%