Abstract
Nature has provided inspiration for most of the man-made technologies. Scientists believe that dolphins are the second to humans in smartness and intelligence. Echolocation is the biological sonar used by dolphins and several kinds of other animals for navigation and hunting in various environments. This ability of dolphins is mimicked in this chapter to develop a new optimization method. There are different metaheuristic optimization methods, but in most of these algorithms, parameter tuning takes a considerable time of the user, persuading the scientists to develop ideas to improve these methods. Studies have shown that metaheuristic algorithms have certain governing rules and knowing these rules helps to get better results. Dolphin echolocation (DE) takes advantages of these rules and outperforms many existing optimization methods, while it has few parameters to be set. The new approach leads to excellent results with low computational efforts [1].
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kaveh A, Farhoudi N (2013) A new optimization method: dolphin echolocation. Adv Eng Softw 59:53–70
Griffin DR (1958) Listening in the dark: the acoustic orientation of bats and men. Yale University Press, New Haven, CT, p 413 [Biological Laboratories, Harvard University, Cambridge. MA]
Au WWL (1993) The sonar of dolphins. Springer, New York
May J (1990) The Greenpeace book of dolphins. Greenpeace Communications Ltd., London
Thomas JA, Moss CF, Vater M (2002) Echolocation in bats and dolphins. University of Chicago Press, Chicago, IL
Kaveh A, Farhoudi N (2011) A unified approach to parameter selection in meta-heuristic algorithms for layout optimization. J Constr Steel Res 67:15453–15462
Kaveh A, Talatahari S (2012) Charged system search for optimal design of planar frame structures. Appl Soft Comput 12:382–393
Wu SJ, Chow PT (1995) Steady-state genetic algorithms for discrete optimization of trusses. Comput Struct 56:979–991
Lee KS, Geem ZW, Lee SH, Bae KW (2005) The harmony search heuristic algorithm for discrete structural optimization. Eng Optim 37:663–684
Li LJ, Huang ZB, Liu F (2009) A heuristic particle swarm optimization method for truss structures with discrete variables. Comput Struct 87:435–443
Kaveh A, Talatahari S (2009) A particle swarm ant colony optimization for truss structures with discrete variables. Comput Struct 87:1129–1140
Construction (AISC) (1989) Manual of steel construction—allowable stress design, 9th edn. AISC, Chicago, IL
Hasançebi O, Çarbaş S, Doğan E, Erdal F, Saka MP (2009) Performance evaluation of metaheuristic search techniques in the optimum design of real size pin jointed structures. Comput Struct 87(5–6):284–302
Kaveh A, Talatahari S (2009) Hybrid algorithm of harmony search, particle swarm and ant colony for structural design optimization. Stud Comput Intell 239:159–198
Sonmez M (2011) Discrete optimum design of truss structures using artificial bee colony algorithm. Struct Multidiscip Optim 43:85–97
ANSI/AISC 360-05 (2005) Specification for structural steel buildings. American Institute of Steel Construction, Chicago, IL, 60601-1802, March 9
Kaveh A, Talatahari S (2010) Optimum design of skeletal structures using imperialist competitive algorithm. Comput Struct 88:1220–1229
Camp CV, Bichon J, Stovall SP (2005) Design of steel frames using ant colony optimization. J Struct Eng ASCE 131(3):369–379
Degertekin SO (2008) Optimum design of steel frames using harmony search algorithm. Struct Multidiscip Optim 36:393–401
Kaveh A, Talatahari S (2010) An improved ant colony optimization for design of planar steel frames. Eng Struct 32:864–876
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Kaveh, A. (2017). Dolphin Echolocation Optimization. In: Advances in Metaheuristic Algorithms for Optimal Design of Structures. Springer, Cham. https://doi.org/10.1007/978-3-319-46173-1_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-46173-1_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-46172-4
Online ISBN: 978-3-319-46173-1
eBook Packages: EngineeringEngineering (R0)