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Cuckoo Search Optimization

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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], 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 others 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 solutions; replacement of the host eggs with respect to the quality of the new solutions or Cuckoo eggs produced based randomization via Lévy flights globally (exploration); and 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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References

  1. Yang XS (2008) Nature-inspired metaheuristic algorithms. Luniver Press, Bristol

    Google Scholar 

  2. Yang XS, Deb S (2009) Cuckoo search via Lévy flights. In: Proceedings of world congress on nature and biologically inspired computing. IEEE Publications, USA, pp 210–214

    Google Scholar 

  3. Yang XS, Deb S (2010) Engineering optimisation by cuckoo search. Int J Math Model Numer Optim 1:330–343

    MATH  Google Scholar 

  4. Kaveh A, Bakhshpoori T (2013) Optimum design of space trusses using cuckoo search. Iranian J Sci Technol C1(37):1–15

    Google Scholar 

  5. Kaveh A, Bakhshpoori T (2013) Optimum design of steel frames using cuckoo search algorithm with Lévy flights. Struct Des Tall Build Spec Struct 22(13):1023–1036

    Article  Google Scholar 

  6. American Institute of Steel Construction (AISC) (1989) Manual of steel construction–allowable stress design, 9th edn. AISC, Chicago

    Google Scholar 

  7. Tuba M, Subotic M, Stanarevic N (2011) Modified cuckoo search algorithm for unconstrained optimization problems. In: Proceedings of the 5th European computing conference (ECC’11), pp 263–268

    Google Scholar 

  8. Camp CV (2007) Design of space trusses using big bang-big crunch optimization. J Struct Eng 133:999–1008

    Article  Google Scholar 

  9. Camp CV, Bichon BJ (2004) Design of space trusses using ant colony optimization. J Struct Eng 130:741–751

    Article  Google Scholar 

  10. Kaveh A, Talatahari S (2010) Optimal design of skeletal structures via the charged system search algorithm. Struct Multidiscip Optim 41:893–911

    Article  Google Scholar 

  11. Lee KS, Geem W (2004) A new structural optimization method based on the harmony search algorithm. Comput Struct 82:781–798

    Article  Google Scholar 

  12. Kaveh A, Talatahari S (2008) Ant colony optimization for design of space trusses. Int J Space Struct 23:167–181

    Article  Google Scholar 

  13. Kaveh A, Talatahari S (2009) Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures. Comput Struct 87:267–283

    Article  Google Scholar 

  14. Kaveh A, Talatahari S (2009) Size optimization of space trusses using Big Bang-Big Crunch algorithm. Comput Struct 87:1129–1140

    Article  Google Scholar 

  15. Kaveh A, Talatahari S (2010) Optimum design of skeletal structures using imperialist competitive algorithm. Comput Struct 88:1220–1229

    Article  Google Scholar 

  16. Kaveh A, Talatahari S (2009) A particle swarm ant colony optimization for truss structures with discrete variables. J Construct Steel Res 65:1558–1568

    Article  Google Scholar 

  17. Camp CV, Bichon BJ, Stovall SP (2005) Design of steel frames using ant colony optimization. J Struct Eng ASCE 131:369–379

    Article  Google Scholar 

  18. AISC (2001) Manual of steel construction: load and resistance factor design. AISC, Chicago

    Google Scholar 

  19. Dumonteil P (1992) Simple equations for effective length factors. Eng J AISE 29(3):1115

    Google Scholar 

  20. Pezeshk S, Camp CV, Chen D (2000) Design of nonlinear framed structures using genetic optimization. J Struct Eng ASCE 126:382–388

    Article  Google Scholar 

  21. Kaveh A, Talatahari S (2010) An improved ant colony optimization for the design of planar steel frames. Eng Struct 32:864–873

    Article  Google Scholar 

  22. Kaveh A, Talatahari S (2010) A discrete Big Bang—Big Crunch algorithm for optimal design of skeletal structures. Asian J Civil Eng 11(1):103–122

    Google Scholar 

  23. Degertekin SO (2008) Optimum design of steel frames using harmony search algorithm. Struct Multidiscip Optim 36:393–401

    Article  Google Scholar 

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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. (2014). Cuckoo Search Optimization. In: Advances in Metaheuristic Algorithms for Optimal Design of Structures. Springer, Cham. https://doi.org/10.1007/978-3-319-05549-7_10

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  • DOI: https://doi.org/10.1007/978-3-319-05549-7_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05548-0

  • Online ISBN: 978-3-319-05549-7

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