Self-organizing migrating algorithm using covariance matrix adaptation evolution strategy for dynamic constrained optimization
Tài liệu tham khảo
Luo, 2019, Gpu based parallel genetic algorithm for solving an energy efficient dynamic flexible flow shop scheduling problem, J. Parallel Distrib. Comput., 133, 244, 10.1016/j.jpdc.2018.07.022
Zhang, 2020, Optimization-based collision avoidance, IEEE Trans. Control Syst. Technol.
Wang, 2019, Evolutionary dynamic constrained optimization: test suite construction and algorithm comparisons, Swarm Evol. Comput., 50, 100559, 10.1016/j.swevo.2019.100559
Malekzadeh Fard, 2019, Optimization of the prismatic core sandwich panel under buckling load and yield stress constraints using an improved constrained differential evolution algorithm, J. Appl. Comput. Mech.
Rao, 2017, Constrained economic optimization of shell-and-tube heat exchangers using Elitist-Jaya algorithm, Energy, 128, 785, 10.1016/j.energy.2017.04.059
Yang, 2010, A clustering particle swarm optimizer for locating and tracking multiple optima in dynamic environments, IEEE Trans. Evol. Comput., 14, 959, 10.1109/TEVC.2010.2046667
Bu, 2016, Continuous dynamic constrained optimization with ensemble of locating and tracking feasible regions strategies, IEEE Trans. Evol. Comput., 21, 14, 10.1109/TEVC.2016.2567644
Arnold, 2012, A (1+1)-cma-es for constrained optimisation, 297
Ivan, 2000, Soma-self-organizing migrating algorithm
Zelinka, 2004, Soma – self-organizing migrating algorithm, 167
Deep, 2008, A self-organizing migrating genetic algorithm for constrained optimization, Appl. Math. Comput., 198, 237, 10.1016/j.amc.2007.08.032
dos Santos Coelho, 2009, Self-organizing migrating strategies applied to reliability-redundancy optimization of systems, IEEE Trans. Reliab., 58, 501, 10.1109/TR.2009.2019514
dos Santos Coelho, 2010, An efficient cultural self-organizing migrating strategy for economic dispatch optimization with valve-point effect, Energy Convers. Manag., 51, 2580, 10.1016/j.enconman.2010.05.022
Singh, 2016, C-somaqi: self organizing migrating algorithm with quadratic interpolation crossover operator for constrained global optimization, 147
Hansen, 2006, The cma evolution strategy: a comparing review, 75
Igel, 2006, A computational efficient covariance matrix update and a (1+1)-cma for evolution strategies, 453
Arnold, 2010, Active covariance matrix adaptation for the (1+1)-cma-es, 385
Suttorp, 2009, Efficient covariance matrix update for variable metric evolution strategies, Mach. Learn., 75, 167, 10.1007/s10994-009-5102-1
Bonyadi, 2013, A hybrid particle swarm with velocity mutation for constraint optimization problems, 1
Maesani, 2015, Memetic viability evolution for constrained optimization, IEEE Trans. Evol. Comput., 20, 125, 10.1109/TEVC.2015.2428292
Spettel, 2018, A covariance matrix self-adaptation evolution strategy for optimization under linear constraints, IEEE Trans. Evol. Comput., 23, 514, 10.1109/TEVC.2018.2871944
Kumar, 2020, A reference vector-based simplified covariance matrix adaptation evolution strategy for constrained global optimization, IEEE Trans. Cybern., 1, 10.1109/TCYB.2020.3013950
Kumar, 2021, A υ-constrained matrix adaptation evolution strategy with Broyden-based mutation for constrained optimization, IEEE Trans. Cybern., 1, 10.1109/TCYB.2020.3042853
Kumar, 2020, A modified covariance matrix adaptation evolution strategy for real-world constrained optimization problems, 11
Hellwig, 2018, A matrix adaptation evolution strategy for constrained real-parameter optimization, 1
Blackwell, 2008, Particle swarms for dynamic optimization problems, 193
Zhu, 2018, Global replacement-based differential evolution with neighbor-based memory for dynamic optimization, Appl. Intell., 48, 3280, 10.1007/s10489-018-1147-9
Blackwell, 2004, Multi-swarm optimization in dynamic environments, 489
Ozsoydan, 2019, Quantum firefly swarms for multimodal dynamic optimization problems, Expert Syst. Appl., 115, 189, 10.1016/j.eswa.2018.08.007
L. Skanderova, T. Fabian, I. Zelinka, Self-organizing migrating algorithm using covariance matrix adaptation evolution strategy for dynamic constrained optimization source codes, 2020.
Carrasco, 2020, Recent trends in the use of statistical tests for comparing swarm and evolutionary computing algorithms: Practical guidelines and a critical review, Swarm Evol. Comput., 54, 100665, 10.1016/j.swevo.2020.100665
Hansen, 2010