Comparative Analysis of the Cuckoo Search Algorithm

  • Pinar Civicioglu
  • Erkan Besdok
Part of the Studies in Computational Intelligence book series (SCI, volume 516)


Cuckoo Search Algorithm (CS) is a population based, elitist evolutionary search algorithm proposed for the solution of numerical optimization problems. Despite its wide use, the algorithmic process of CS has been scarcely studied in detail. In this chapter, the algorithmic structure of CS and its effective problem solving success have been studied. Fifty benchmark problems were used in the numerical tests performed in order to study the algorithmic behavior of CS. The success of CS in solving benchmark problems was compared with three widely used optimization algorithms (i.e., PSO, DE, and ABC) by means of Kruskal–Wallis statistical test. The search strategy of CS, which utilizes the Lèvy distribution, enables it to analyze the search space in a very successful manner. The statistical results have verified that CS has the superior problem-solving ability as a search strategy.


Cuckoo search Stable distributions Lèvy-walk  Kruskal–Wallis test 



The studies in this chapter have been supported within the scope of the scientific research project of 110Y309 supported by TUBITAK.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.College of Aviation, Department of Aircraft Electrics and ElectronicsErciyes UniversityKayseriTurkey
  2. 2.Department of Geomatic EngineeringErciyes UniversityKayseriTurkey

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