- Volume 1 Issue 2
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 for navigation and hunting in various environments. This ability of dolphins is mimicked in this paper to develop a new optimization method. Dolphin Echolocation Optimization (DEO) is an optimization method based on dolphin's approach for hunting food and exploration of environment. DEO has already been developed for discrete optimization search space and here it is extended to continuous search space. DEO has simple rules and is adjustable for predetermined computational cost. DEO provides the optimum results and leads to alternative optimality curves suitable for the problem. This algorithm has a few parameters and it is applicable to a wide range of problems like other metaheuristic algorithms. In the present work, the efficiency of this approach is demonstrated using standard benchmark problems.
Dolphin Echolocation Optimization;continuous search space;mathematical examples;truss structure
- Au, W.W.L. and Simmons, J. (2007), "Echolocation in dolphins and bats", Phys Today, 60(9), 40-45.
- Dorigo, M, Maniezzo, V. and Colorni, A. (1996), "The ant system: optimization by a colony of cooperating agents", IEEE Trans. Syst. Man Cybern., B26, 29-41.
- Eberhart, R.C. and Kennedy, J. (1995), "A new optimizer using particle swarm theory", Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan.
- Erol, O.K. and Eksin, I. (2006), "New optimization method: Big Bang-Big Crunch", Adv. Eng. Softw., 37(2), 106-111. https://doi.org/10.1016/j.advengsoft.2005.04.005
- Fogel, L.J., Owens, A.J. and Walsh, M.J. (1966), Artificial intelligence through simulated evolution, Wiley, Chichester, UK.
- Goldberg, D.E. (1989), Genetic algorithms in search optimization and machine learning, Addison-Wesley, Boston, USA.
- Goncalves, M.S., Lopez, R.H. and Miguel, L.F.F. (2015), "Search group algorithm: A new metaheuristic method for the optimization of truss structures", Comput. Struct., 153, 165-184. https://doi.org/10.1016/j.compstruc.2015.03.003
- Holland, J.H. (1975), Adaptation in natural and artificial systems, University of Michigan Press, Ann Arbor.
- Lee, K.S. and Geem, Z.W. (2004) "A new structural optimization method based on the harmony search algorithm", Comput. Struct., 82(9), 781-798. https://doi.org/10.1016/j.compstruc.2004.01.002
- Kaveh, A. and Farhoudi, N. (2013), "A new optimization method: Dolphin echolocation", Adv. Eng. Softw., 59, 53-70. https://doi.org/10.1016/j.advengsoft.2013.03.004
- Kaveh, A. and Farhoudi, N. (2011), "A unified approach to parameter selection in meta-heuristic algorithms for layout optimization", J. Constr. Steel Res., 67(10), 15453-15462.
- Kaveh, A. and Ilchi Ghazaan, M. (2015), "Truss optimization with dynamic constraints using UECBO", Adv. Comput. Des., Techno Press, Accepted for publication, 2015.
- Kaveh, A. and Khayatazad, M. (2013), "Ray optimization for size and shape optimization of truss structures", Comput. Struct., 117, 82-94. https://doi.org/10.1016/j.compstruc.2012.12.010
- Kaveh, A. and Mahdavai, V.R. (2014), "Colliding bodies optimization method for optimum design of truss structures with continuous variables", Adv. Eng. Softw., 70, 1-12. https://doi.org/10.1016/j.advengsoft.2014.01.002
- Kaveh, A. and Maniat, M. (2015), "Damage detection based on MCSS and PSO using modal data", Smart Struct. Syst., 15(5), 1253-1270. https://doi.org/10.12989/sss.2015.15.5.1253
- Kaveh, A. and Talatahari, S. (2009), "Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures", Comput. Struct., 87(5), 267-283. https://doi.org/10.1016/j.compstruc.2009.01.003
- Kaveh, A. and Talatahari, S. (2010), "A novel heuristic optimization method: charged system search", Acta Mech., 213(3-4), 267-286. https://doi.org/10.1007/s00707-009-0270-4
- Kaveh, A. and Zolghadr, A. (2014), "A new PSRO algorithm for frequency constraint truss shape and size optimization", Struct. Eng. Mech., 52(3), 445-468. https://doi.org/10.12989/sem.2014.52.3.445
- Koza, J.R. (1990), Genetic programming: a paradigm for genetically breeding populations of computer programs to solve problems, Report No. STAN-CS-90-1314, Stanford University, Stanford, CA.
- Mirjalili, S. (2015), "The ant lion optimizer", Adv. Eng. Softw., 83, 80-98. https://doi.org/10.1016/j.advengsoft.2015.01.010
- Rao, R.V., Savsani, V.J. and Vakharia, D.P. (2011) "Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems", Comput. Aid. Des., 43(3), 303-315. https://doi.org/10.1016/j.cad.2010.12.015
- Sadollah, A., Eskandar, H., Bahreininejad, A. and Kim, J.H. (2015), "Water cycle, mine blast and improved mine blast algorithms for discrete sizing optimization of truss structures", Comput. Struct., 149, 1-16. https://doi.org/10.1016/j.compstruc.2014.12.003
- Tsoulos, I.G. (2008), "Modifications of real code genetic algorithm for global optimization", Appl. Math. Comput., 203(2), 598-607. https://doi.org/10.1016/j.amc.2008.05.005
- Yang, X.S. (2010), "A new metaheuristic bat-inspired algorithm", NICSO, 284, 65-74.
- Yang, X.S. and Deb, S. (2009), "Engineering optimisation by cuckoo search", Int. J. Math. Model. Num. Optim., 1(4), 330-343.
- Yang, X.S. (2011), "Bat algorithm for multi-objective optimization", Int. J. Bio-Inspired Comput., 3(5), 267-274. https://doi.org/10.1504/IJBIC.2011.042259
- May, J. (1990), The greenpeace book of dolphins, Greenpeace Communications Ltd.