Multiple adaptive strategies based particle swarm optimization algorithm

Ser, 2019, Bio-inspired computation: where we stand and what's next, Swarm Evol. Compt., 48, 220, 10.1016/j.swevo.2019.04.008 Rajasekhar, 2017, Computing with the collective intelligence of honey bees C A survey, Swarm Evol. Compt., 32, 25, 10.1016/j.swevo.2016.06.001 Eberhart, 1995, A new optimizer using particle swarm theory, 39 Kennedy, 1995, Particle swarm optimization, 1942 Ciuprina, 2002, Use of intelligent-particle swarm optimization in electormagnetics, IEEE Trans. Magn., 38, 1037, 10.1109/20.996266 Ling, 2004, Hybrid particle swarm optimization with wavelet mutation and its industrial applications, IEEE Trans. Syst. Man Cybern. B Cybern., 34, 997 Soh, 2010, Discovering unique, low-energy pure water isomers: memetic exploration, optimization and landscape analysis, IEEE Trans. Evol. Comput., 14, 419, 10.1109/TEVC.2009.2033584 Kadirkamanathan, 2006, Stability analysis of the particle dynamics in particle swarm optimizer, IEEE Trans. Evol. Comput., 10, 245, 10.1109/TEVC.2005.857077 Kennedy, 1999, Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance, 1931 Ratnaweera, 2004, Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients, IEEE Trans. Evol. Comput., 8, 240, 10.1109/TEVC.2004.826071 Kennedy, 2002, Population structure and particle swarm performance, 1671 Tanabe, 2014, Improving the search performance of SHADE using linear population size reduction, 1658 Zhu, 2013, Adaptive population tuning scheme for differential evolution, Inf. Sci., 223, 164, 10.1016/j.ins.2012.09.019 Eiben, 2006, Is self-adaptation of selection pressure and population size possible - a case study, 900 Hansen, 2003, Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (cma-es), Evol. Comput., 11, 1, 10.1162/106365603321828970 Samal, 2007, A closed loop stability analysis and parameter selection of the particle swarm optimization dynamics for faster convergence, 1769 Shi, 1998, A modified particle swarm optimizer, 68 Harrison, 2018, Self-adaptive particle swarm optimization: a review and analysis of convergence, Swarm Intell, 12, 187, 10.1007/s11721-017-0150-9 Zhan, 2009, Adaptive particle swarm optimization, IEEE Trans. Syst. Man Cybern. B Cybern., 39, 1362, 10.1109/TSMCB.2009.2015956 W.B. Liu, Z.D. Wang, Y. Yuan, N.Y. Zeng, K. Hone, X.H. Liu, A novel sigmoid-function-based adaptive weighted particle swarm optimizer, IEEE Trans. Cybern. doi: 10.1109/TCYB.2019.2925015 Xia, 2019, A fitness-based multi-rule particle swarm optimization, Swarm Evol. Compt., 44, 349, 10.1016/j.swevo.2018.04.006 Hashemi, 2011, A note on the learning automata based algorithms for adaptive parameter selection in PSO, Appl. Soft Comput., 11, 689, 10.1016/j.asoc.2009.12.030 Xia, 2020, An expanded particle swarm optimization based on multi-exemplar and forgetting ability, Inf. Sci., 508, 105, 10.1016/j.ins.2019.08.065 Juang, 2011, Adaptive fuzzy particle swarm optimization for global optimization of multimodal functions, Inf. Sci., 181, 4539, 10.1016/j.ins.2010.11.025 Tanweer, 2015, Self regulating particle swarm optimization algorithm, Inf. Sci., 294, 182, 10.1016/j.ins.2014.09.053 Mendes, 2004, The fully informed particle swarm: simpler,maybe better, IEEE Trans. Evol. Comput., 8, 204, 10.1109/TEVC.2004.826074 Liang, 2006, Comprehensive learning particle swarm optimizer for global optimization of multimodal functions, IEEE Trans. Evol. Comput., 10, 281, 10.1109/TEVC.2005.857610 Zhan, 2011, Orthogonal learning particle swarm optimization, IEEE Trans. Evol. Comput., 15, 832, 10.1109/TEVC.2010.2052054 Wang, 2018, Particle swarm optimization algorithm: an overview, Soft Comput., 387, 10.1007/s00500-016-2474-6 Jin, 2013, Particle swarm optimization using dimension selection methods, Appl. Math. Comput., 219, 5185 Liang, 2005, Dynamic multi-swarm particle swarm optimizer, 124 Zhao, 2010, Dynamic multi-swarm particle swarm optimizer with subregional harmony search, 1983 Liu, 2017, Ecosystem particle swarm optimization, Soft Comput., 21, 1667, 10.1007/s00500-016-2111-4 Lynn, 2015, Heterogeneous comprehensive learning particle swarm optimization with enhanced exploration and exploitation, Swarm Evol. Comput., 24, 11, 10.1016/j.swevo.2015.05.002 Bonyadi, 2017, Particle swarm optimization for single objective continuous space problems: a review, Evol. Comput., 25, 1, 10.1162/EVCO_r_00180 Angeline, 1998, Using selection to improve particle swarm optimization, 84 Gong, 2016, Genetic learning particle swarm optimization, IEEE Trans. Cybern., 46, 2277, 10.1109/TCYB.2015.2475174 X.W. Xia, L. Gui, F. Yu, H.R. Wu, B. Wei, Y.L. Zhang, Z.H. Zhan, Triple archives particle swarm optimization, IEEE Trans. Cybern. doi: 10.1109/TCYB.2019.2943928 Qu, 2012, Niching particle swarm optimization with local search for multi-modal optimization, Inf. Sci., 197, 131, 10.1016/j.ins.2012.02.011 Wang, 2010, Improving particle swarm optimization performance with local search for high-dimensional function optimization, Optim. Methods Software, 25, 781, 10.1080/10556780903034514 Xia, 2014, An improved particle swarm optimizer based on tabu detecting and local learning strategy in a shrunk search space, Appl. Soft Comput., 23, 76, 10.1016/j.asoc.2014.06.012 Lynn, 2017, Ensemble particle swarm optimizer, Appl, Soft Comput., 55, 533, 10.1016/j.asoc.2017.02.007 Xin, 2010, An adaptive hybrid optimizer based on particle swarm and differential evolution for global optimization, Sci. China E, 53, 980 Xin, 2012, Hybridizing differential evolution and particle swarm optimization to design powerful optimizers: a review and taxonomy, IEEE Trans. Syst. Man Cybern. C Appl. Rev., 42, 744, 10.1109/TSMCC.2011.2160941 Kiran, 2013, A recombination-based hybridization of particle swarm optimization and artificial bee colony algorithm for continuous optimization problems, Appl. Soft Comput., 13, 2188, 10.1016/j.asoc.2012.12.007 Kela, 2014, Reliability optimization of radial distribution systems employing differential evolution and bare bones particle swarm optimization, J. Inst. Eng. India Ser. B., 95, 231, 10.1007/s40031-014-0094-z Sayah, 2013, A hybrid differential evolution algorithm based on particle swarm optimization for nonconvex economic dispatch problems, Appl. Soft Comput., 13, 1608, 10.1016/j.asoc.2012.12.014 Marco, 2009, A composite particle swarm optimization algorithm, IEEE Trans. Evol. Comput., 13, 1120, 10.1109/TEVC.2009.2021465 de Oca, 2011, Incremental social learning in particle swarms, IEEE Trans. Syst. Man Cybern. B Cybern., 42, 368, 10.1109/TSMCB.2010.2055848 Peram, 2003, Fitness-distance-ratio based particle swarm optimization, 174 Wu, 2016, Differential evolution with multi population based ensemble of mutation strategies, Inf. Sci., 329, 329, 10.1016/j.ins.2015.09.009 Storn, 1997, Differential evolution: a simple and efficient heuristic for global optimization over continuous spaces, J. Global Optim., 11, 341, 10.1023/A:1008202821328 Das, 2016, Recent advances in differential evolution-an updated survey, Swarm Evol, Comput. Times, 27, 1 Zhang, 2009, JADE: adaptive differential evolution with optional external archive, IEEE Trans. Evol. Comput., 13, 945, 10.1109/TEVC.2009.2014613 Li, 2015, Competitive and cooperative particle swarm optimization with information sharing mechanism for global optimization problems, Inf. Sci., 293, 370, 10.1016/j.ins.2014.09.030 Liang, 2013, Problem definitions and evaluation criteria for the CEC 2013 special session on real-parameter optimization, Nanyang Technological Univ., Singapore, Tech. Rep. Awad, 2016, Problem definitions and evaluation criteria for the CEC 2017 special session and competition on single objective real-parameter numerical optimization, Nanyang Technological Univ., Singapore, Tech. Rep. 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