2013
DOI: 10.1007/978-3-319-02141-6_3
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Cuckoo Search: A Brief Literature Review

Abstract: Cuckoo search (CS) was introduced in 2009, and it has attracted great attention due to its promising efficiency in solving many optimization problems and real-world applications. In the last few years, many papers have been published regarding cuckoo search, and the relevant literature has expanded significantly. This chapter summarizes briefly the majority of the literature about cuckoo search in peer-reviewed journals and conferences found so far. These references can be systematically classified into approp… Show more

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Cited by 116 publications
(53 citation statements)
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References 86 publications
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“…As a robust and computationally efficient algorithm, ODCDM has been adopted by state-of-the-art industrial products and has been applied in real distribution networks [6,13,14]. Cuckoo Search is one of the most advanced meta-heuristic algorithms, and it has been successfully applied in almost every area and domain of optimization problems [15]. Previous research demonstrated that CS outperforms some popular meta-heuristic algorithms, such as GA and Particle Swarm Optimization (PSO) in different areas [16].…”
Section: Algorithm Selection and Implementationmentioning
confidence: 99%
See 1 more Smart Citation
“…As a robust and computationally efficient algorithm, ODCDM has been adopted by state-of-the-art industrial products and has been applied in real distribution networks [6,13,14]. Cuckoo Search is one of the most advanced meta-heuristic algorithms, and it has been successfully applied in almost every area and domain of optimization problems [15]. Previous research demonstrated that CS outperforms some popular meta-heuristic algorithms, such as GA and Particle Swarm Optimization (PSO) in different areas [16].…”
Section: Algorithm Selection and Implementationmentioning
confidence: 99%
“…There is a chance that some generated solutions are far enough from the current best solution, which can make sure the system will not be trapped in a local optimum. The original CS algorithm was developed to solve the optimization problems with continuous variables only, and it can be revised to solve combinatorial problems and mixed integer optimization problems [15]. Basically, the progress for continuous variables is kept the same, and for discrete variables, the step size is rounded off before being used to generate the new values for the discrete variables.…”
Section: Cuckoo Search Via Lévy Flightsmentioning
confidence: 99%
“…For example, if a host bird discovers the eggs which are not their own, it will either throw these alien eggs away or simply abandon its nest and build a new nest elsewhere. Some cuckoo species such as the New World broodparasitic Tapera have evolved in such a way that female parasitic cuckoos are often very specialized in the mimicry in colors and pattern of the eggs of a few chosen host species [14].…”
Section: Particle Swarm Optimizationmentioning
confidence: 99%
“…Some applications of metaheuristic algorithms include neural networks, data mining, industrial, mechanical, electrical, and software engineering, as well as certain problems from location theory [14][15][16][17][18][19][20][21]. The most interesting and most widely used metaheuristic algorithms are swarm-intelligence algorithms which are based on a collective intelligence of colonies of ants, termites, bees, flock of birds, and so forth [22].…”
Section: Introductionmentioning
confidence: 99%