Grasshopper Optimisation Algorithm: Theory and application

Advances in Engineering Software - Tập 105 - Trang 30-47 - 2017
Shahrzad Saremi1,2, Seyedali Mirjalili1,2, Andrew Lewis2
1Griffith College, Mt Gravatt, Brisbane, QLD 4122, Australia
2School of Information and Communication Technology, Griffith University, Nathan, Brisbane, QLD 4111, Australia

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

Mirjalili, 2014, Grey wolf optimizer, Adv Eng Softw, 69, 46, 10.1016/j.advengsoft.2013.12.007

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.

Glover, 1989, Tabu search-part I, ORSA J Comput, 1, 190, 10.1287/ijoc.1.3.190

H.R. Lourenço, O.C. Martin, and T. Stutzle, ``Iterated local search,'' arXiv preprint math/0102188, 2001.

Holland, 1992, Genetic algorithms, Sci Am, 267, 66, 10.1038/scientificamerican0792-66

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.

Rashedi, 2009, GSA: a gravitational search algorithm, Inf Sci, 179, 2232, 10.1016/j.ins.2009.03.004

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

Mirjalili, 2015, The ant lion optimizer, Adv Eng Softw, 83, 80, 10.1016/j.advengsoft.2015.01.010

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

Sadollah, 2012, Mine blast algorithm for optimization of truss structures with discrete variables, Comput Struct, 102, 49, 10.1016/j.compstruc.2012.03.013