Kennedy J, Eberhart R. Particle swarm optimization[C]. Proc IEEE Int Conf on Neural Networks. Perth: Perth IEEE Press, 1995: 1942-1948.
[2]
Qu B Y, Suganthan P N, Das S. A distance-based locally informed particle swarm model for multimodal optimization[J]. IEEE Trans on Evolutionary Computation, 2013, 17(3): 387-402.
(Wen T, Sheng G J, Guo Q, et al. Web service composition based on modified particle swarm optimization[J]. Chinese J of Computers, 2013, 36(5): 1031-1046.)
(Xu X B, Jiang Q Q, Zheng K F, et al. IDS alert clustering algorithm based on chaotic particle swarm optimization[J]. J on Communications, 2013, 34(3): 105-110.)
[7]
Sadeghi J, Sadeghi S, Niaki S T A. Optimizing a hybrid vendor-managed inventory and transportation problem with fuzzy demand: An improved particle swarm optimization algorithm[J]. Information Sciences, 2014, 272: 126-144.
[8]
Nedic V, Cvetanovic S, Despotovic D, et al. Data mining with various optimization methods[J]. Expert Systems with Applications, 2014, 41(8): 3993-3999.
[9]
Feng H M, Liao K L. Hybrid evolutionary fuzzy learning scheme in the applications of traveling salesman problems[J]. Information Sciences, 2014, 270: 204-225.
[10]
Jin X, Liang Y Q, Tian D P, et al. Particle swarm optimization using dimension selection methods[J]. Applied Mathematics and Computation, 2013, 219(10): 5185-5197.
[11]
Xu G. An adaptive parameter tuning of particle swarm optimization algorithm[J]. Applied Mathematics and Computation, 2013, 219(9): 4560-4569.
[12]
Beheshti Z, Hj Shamsuddin S M. CAPSO: Centripetal accelerated particle swarm optimization[J]. Information Sciences, 2014, 258: 54-79.
[13]
Liang J J, Qin A K, Suganthan P N. Comprehensive learning particle swarm optimizer for global optimization of multimodal functions[J]. IEEE Trans on Evolutionary Computation, 2006, 10(3): 281-295.
(Zhu X H, Li Y H, Li N, et al. Improved PSO algorithm based on swarm prematurely degree and nonlinear periodic oscillating strategy[J]. J on Communications, 2014, 35(2): 182-189.)
[16]
Li N J, WangW J, James Hsu C C, et al. Enhanced particle swarm optimizer incorporating a weighted particle[J]. Neurocomputing, 2014, 124: 218-227.
[17]
Liu H, Ding G, Wang B. Bare-bones particle swarm optimization with disruption operator[J]. Applied Mathematics and Computation, 2014, 238: 106-122.
[18]
Han F, Liu Q. A diversity-guided hybrid particle swarm optimization based on gradient search[J]. Neurocomputing, 2014, 137: 234-240.
[19]
McKayMD, Beckman R J, ConoverWJ. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code[J]. Technometrics, 1979, 21(2): 239-245.
(Liu Y, Tian X F, Zhan Z H, et al. Research on inertia weight control approaches in particle swarm optimization[J]. J of Nanjing University: Natural Sciences, 2011, 47(4): 364-371.)
(Zhang Z J, Luo C Y, Zhang F, et al. Particle swarm optimization with oscillating parameter strategy[J]. J of Chongqing University, 2011, 34(6): 36-41.)
(Jin M, Lu H X. A multi-subgroup hierarchical hybrid of genetic algorithm and particle swarm optimization[J]. Control Theory & Applications, 2013, 30(10): 1231-1238.)
[26]
Qu B Y, Liang J J, Suganthan P N. Niching particle swarm optimization with local search for multi-modal optimization[J]. Information Sciences, 2012, 197: 131-143.
[27]
Li M, Kang H, Zhou P. Hybrid optimization algorithm based on chaos, cloud and particle swarm optimization algorithm [J]. J of Systems Engineering and Electronics, 2013, 24(2): 324-334.
[28]
Van den Bergh F, Engelbrecht A P. A cooperative approach to particle swarm optimization[J]. IEEE Trans on Evolutionary Computation, 2004, 8(3): 225-239.
(Jiang J G, Li J, Long X P, et al. A shuffled frog leaping algorithm using niche technology[J]. Chinese J of Computational Mechanics, 2012, 29(6): 960-965.)
