Grasshopper Optimisation Algorithm: Theory and application
Tóm tắt
Từ khóa
Tài liệu tham khảo
Coello Coello, 2002, Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art, Comput Meth Appl Mech Eng, 191, 1245, 10.1016/S0045-7825(01)00323-1
Marler, 2004, Survey of multi-objective optimization methods for engineering, Struct Multidiscipl Optim, 26, 369, 10.1007/s00158-003-0368-6
Spall, 2005, vol. 65
Dasgupta, 1997
Yang, 2010
Mirjalili, 2013, S-shaped versus V-shaped transfer functions for binary particle swarm optimization, Swarm Evol Comput, 9, 1, 10.1016/j.swevo.2012.09.002
Davis, 1991, Bit-climbing, representational bias, and test suite design, ICGA, 18
Kirkpatrick, 1983, Optimization by simmulated annealing, Science, 220, 671, 10.1126/science.220.4598.671
L.J. Fogel, A.J. Owens, and M.J. Walsh, "Artificial intelligence through simulated evolution," 1966.
H.R. Lourenço, O.C. Martin, and T. Stutzle, ``Iterated local search,'' arXiv preprint math/0102188, 2001.
Eberhart, 1995, A new optimizer using particle swarm theory, 39
Colorni, 1991, Distributed optimization by ant colonies, 134
Storn, 1997, Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces, J Glob Optim, 11, 341, 10.1023/A:1008202821328
Eiben, 1998, On evolutionary exploration and exploitation, Fundamenta Informaticae, 35, 35, 10.3233/FI-1998-35123403
Kaveh, 2013, A new optimization method: dolphin echolocation, Adv Eng Softw, 59, 53, 10.1016/j.advengsoft.2013.03.004
Kaveh, 2016, Dolphin monitoring for enhancing metaheuristic algorithms: layout optimization of braced frames, Comput Struct, 165, 1, 10.1016/j.compstruc.2015.11.012
Yang, 2010, Firefly algorithm, stochastic test functions and design optimisation, Int J Bio Inspired Comput, 2, 78, 10.1504/IJBIC.2010.032124
Yang, 2010, Firefly algorithm, Levy flights and global optimization, 209
Yang, 2010, A new metaheuristic bat-inspired algorithm, 65
Yang, 2009, Cuckoo search via Lévy flights, 210
Yang, 2010, Engineering optimisation by cuckoo search, Int J Math Model Numer Optim, 1, 330
Cuevas, 2014, An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation, Appl Intel, 40, 256, 10.1007/s10489-013-0458-0
Cuevas, 2013, A novel evolutionary algorithm inspired by the states of matter for template matching, Expert Syst Appl, 40, 6359, 10.1016/j.eswa.2013.05.055
Yang, 2012, Flower pollination algorithm for global optimization, 240
Wolpert, 1997, No free lunch theorems for optimization, Evol Comput IEEE Trans, 1, 67, 10.1109/4235.585893
Chen, 2009, Locust Swarms-A new multi-optima search technique, 1745
Chen, 2009, An analysis of locust swarms on large scale global optimization problems, 211
Chen, 2010, Improving the performance of particle swarms through dimension reductions—A case study with locust swarms, 1
Lewis, 2009, LoCost: a spatial social network algorithm for multi-objective optimisation, 2866
Cuevas, 2016, Optimization based on the behavior of locust swarms, 101
BoussaïD, 2013, A survey on optimization metaheuristics, Inf Sci, 237, 82, 10.1016/j.ins.2013.02.041
Gogna, 2013, Metaheuristics: review and application, J Exp Theor Artif Intel, 25, 503, 10.1080/0952813X.2013.782347
Zhou, 2011, Multiobjective evolutionary algorithms: A survey of the state of the art, Swarm Evol Comput, 1, 32, 10.1016/j.swevo.2011.03.001
Simpson, 1999, A behavioural analysis of phase change in the desert locust, Biol Rev, 74, 461, 10.1017/S000632319900540X
Rogers, 2003, Mechanosensory-induced behavioural gregarization in the desert locust Schistocerca gregaria, J Exp Biol, 206, 3991, 10.1242/jeb.00648
Topaz, 2008, A model for rolling swarms of locusts, Eur Phys J Special Top, 157, 93, 10.1140/epjst/e2008-00633-y
Yao, 1999, Evolutionary programming made faster, 3, 82
Digalakis, 2001, On benchmarking functions for genetic algorithms, Int J Comput Math, 77, 481, 10.1080/00207160108805080
M. Molga and C. Smutnicki, "Test functions for optimization needs," Test functions for optimization needs, 2005.
X.-S. Yang, "Test problems in optimization," arXiv preprint arXiv:1008.0549, 2010.
P.N. Suganthan, N. Hansen, J.J. Liang, K. Deb, Y.-P. Chen, A. Auger, et al., "Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization," KanGAL report, vol. 2005005, p. 2005, 2005.
Kaveh, 2014, Colliding Bodies Optimization, 195
Kaveh, 2014, Colliding bodies optimization: a novel meta-heuristic method, Comput Struct, 139, 18, 10.1016/j.compstruc.2014.04.005
Kaveh, 2016, A new metaheuristic for continuous structural optimization: water evaporation optimization, Struct Multidiscipl Optim, 1
Kaveh, 2014, An efficient hybrid particle swarm and swallow swarm optimization algorithm, Comput Struct, 143, 40, 10.1016/j.compstruc.2014.07.012
Kaveh, 2012, A new meta-heuristic method: ray optimization, Comput Struct, 112, 283, 10.1016/j.compstruc.2012.09.003
Kaveh, 2013, Ray optimization for size and shape optimization of truss structures, Comput Struct, 117, 82, 10.1016/j.compstruc.2012.12.010
Kaveh, 2014, A new hybrid meta-heuristic for structural design: ranked particles optimization, Struct Eng Mech, 52, 405, 10.12989/sem.2014.52.2.405
Kaveh, 2010, A novel heuristic optimization method: charged system search, Acta Mech, 213, 267, 10.1007/s00707-009-0270-4
Kaveh, 2015, An improved magnetic charged system search for optimization of truss structures with continuous and discrete variables, Appl Soft Comput, 28, 400, 10.1016/j.asoc.2014.11.056
Gandomi, 2013, Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems, Eng Comput, 29, 17, 10.1007/s00366-011-0241-y
Sadollah, 2013, Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems, Appl Soft Comput, 13, 2592, 10.1016/j.asoc.2012.11.026
Zhang, 2008, Differential evolution with dynamic stochastic selection for constrained optimization, Inf Sci, 178, 3043, 10.1016/j.ins.2008.02.014
Liu, 2010, Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization, Appl Soft Comput, 10, 629, 10.1016/j.asoc.2009.08.031
Ray, 2001, Engineering design optimization using a swarm with an intelligent information sharing among individuals, Eng Optim, 33, 735, 10.1080/03052150108940941
Tsai, 2005, Global optimization of nonlinear fractional programming problems in engineering design, Eng Optim, 37, 399, 10.1080/03052150500066737
Chickermane, 1996, Structural optimization using a new local approximation method, Int J Numer Methods Eng, 39, 829, 10.1002/(SICI)1097-0207(19960315)39:5<829::AID-NME884>3.0.CO;2-U
Cheng, 2014, Symbiotic organisms search: A new metaheuristic optimization algorithm, Comput Struct, 139, 98, 10.1016/j.compstruc.2014.03.007
Li, 2009, A heuristic particle swarm optimization method for truss structures with discrete variables, Comput Struct, 87, 435, 10.1016/j.compstruc.2009.01.004
Kaveh, 2009, A particle swarm ant colony optimization for truss structures with discrete variables, J Constr Steel Res, 65, 1558, 10.1016/j.jcsr.2009.04.021