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Cuckoo Search Optimization

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Book cover Advances in Metaheuristic Algorithms for Optimal Design of Structures

Abstract

In this chapter, a metaheuristic method so-called cuckoo search (CS) algorithm is utilized to determine optimum design of structures for both discrete and continuous variables. This algorithm is recently developed by Yang [1] and Yang and Deb [2, 3], and it is based on the obligate brood parasitic behavior of some cuckoo species together with the Lévy flight behavior of some birds and fruit flies. The CS is a population-based optimization algorithm and, similar to many other metaheuristic algorithms, starts with a random initial population which is taken as host nests or eggs. The CS algorithm essentially works with three components: Selection of the best by keeping the best nests or solutionsReplacement of the host eggs with respect to the quality of the new solutions or cuckoo eggs produced based randomization via Lévy flights globally (exploration)Discovering of some cuckoo eggs by the host birds and replacing according to the quality of the local random walks (exploitation) [2]

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Authors and Affiliations

  1. School of Civil Engineering, Centre of Excellence for Fundamental Studies in Structural Engineering, Iran University of Science and Technology, Tehran, Iran

    A. Kaveh

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  1. A. Kaveh
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Kaveh, A. (2017). Cuckoo Search Optimization. In: Advances in Metaheuristic Algorithms for Optimal Design of Structures. Springer, Cham. https://doi.org/10.1007/978-3-319-46173-1_10

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  • DOI: https://doi.org/10.1007/978-3-319-46173-1_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46172-4

  • Online ISBN: 978-3-319-46173-1

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