[1] Kennedy J, Eberhart R C. Particle swarm optimization[C]// Proceedings of the 1995 IEEE International Conference on Neural Network. Piscataway: IEEE, 1995: 1942-1948.
[2] Zhan Z H, Feng X L, Gong Y J, et al. Solving the flight frequency programming problem with particle swarm optim-ization[C]//Proceedings of the 11th Conference on Congress on Evolutionary Computation. Piscataway: IEEE, 2009: 1383-1390.
[3] Lee J H, Song J Y, Kim D W, et al. Particle swarm optim-ization algorithm with intelligent particle number control for optimal design of electric machines[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2018, 65(2): 1791-1798.
[4] Zahra B. A time-varying mirrored S-shaped transfer function for binary particle swarm optimization[J]. Information Sciences, 2020, 512: 1503-1542.
[5] Huo L, Lu Y L. Improved particle swarm optimization for Android malware detection[J]. Computer Engineering and Applications, 2020, 56(7): 96-101.霍林, 陆寅丽. 改进粒子群算法应用于Android恶意应用检测[J]. 计算机工程与应用, 2020, 56(7): 96-101.
[6] Shi Y, Eberhart R C. Parameters selections in particle swarm optimization[C]//Proceedings of the 1998 IEEE International Conference on Evolutionary Programming. Berlin, Heidelberg: Springer, 1998: 591-600.
[7] Deng Z C, Sun H, Zhao J, et al. Stochastic single-dimen-sional mutated particle swarm optimization with dynamic subspace[J]. Journal of Frontiers of Computer Science and Technology, 2020, 14(8): 1409-1426.邓志诚, 孙辉, 赵嘉, 等. 具有动态子空间的随机单维变异粒子群算法[J]. 计算机科学与探索, 2020, 14(8): 1409-1426.
[8] Zhou R, Li J, Wang H. Reverse learning particle swarm optimization based on grey wolf optimization[J]. Computer Engineering and Applications, 2020, 57(6): 48-56.周蓉, 李俊, 王浩. 基于灰狼优化的反向学习粒子群算法[J]. 计算机工程与应用, 2020, 57(6): 48-56.
[9] Zhang X Y, Hu X M, Lin Y. Comparisons of genetic algorithm and particle swarm optimization[J]. Journal of Frontiers of Computer Science and Technology, 2014, 8(1): 90-102.张鑫源, 胡晓敏, 林盈. 遗传算法和粒子群优化算法的性能对比分析[J]. 计算机科学与探索, 2014, 8(1): 90-102.
[10] Deng L B, Zhang L L, Fu N, et al. ERG-DE: an elites regeneration framework for differential evolution[J]. Infor-mation Sciences, 2020, 539: 81-103.
[11] Tang L Y, Mao L, Zhou C X. Improved artificial bee colony algorithm for function optimization[J]. Journal of Frontiers of Computer Science and Technology, 2015, 9(7): 854-860.唐凌芸, 毛力, 周长喜. 求解函数优化问题的改进人工蜂群算法[J]. 计算机科学与探索, 2015, 9(7): 854-860.
[12] Asada M. Modeling early vocal development through infant-caregiver interaction: a review[J]. IEEE Transactions on Cognitive & Developmental Systems, 2016, 8(2): 128-138.
[13] Liang J J, Qin A K, Suganthan P N, et al. Comprehensive learning particle swarm optimizer for global optimization of multimodal functions[J]. IEEE Transactions on Evolu-tionary Computation, 2006, 10(3): 281-295.
[14] Gu K J. Development and application of gravity model in international economics[J]. The Journal of World Economy, 2001, 24(2): 14-25.谷克鉴. 国际经济学对引力模型的开发与应用[J]. 世界经济, 2001, 24(2): 14-25.
[15] Xia X W, Gui L, He G L, et al. An expanded particle swarm optimization based on multi-exemplar and forgetting ability [J]. Information Sciences, 2019, 508: 105-120.
[16] Tanweer M R, Suresh S, Sundararajan N. Self-regulating particle swarm optimization algorithm[J]. Information Sciences, 2015, 294: 182-202.
[17] Liang J J, Qu B Y, Suganthan P N. Problem definitions and evaluation criteria for the CEC 2013 special session on real-parameter optimization: technical report 201212[R]. Singapore: Nanyang Technological University, 2013.
[18] Marco A, Montes O, Thomas S, et al. Frankenstein's PSO: a composite particle swarm optimization algorithm[J]. IEEE Transactions on Evolutionary Computation, 2009, 13(5): 1120-1132.
[19] Zhan Z H, Li Y, Shi Y H. Orthogonal learning particle swarm optimization[J]. IEEE Transactions on Evolutionary Computation, 2011, 15(6): 832-847.
[20] Xin B, Chen J, Zhang J, et al. Hybridizing differential evolution and particle swarm optimization to design powerful optimizers: a review and taxonomy[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 2012, 42(5): 744-767.
[21] 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.
[22] Li Y, Zhan Z H, Lin S, et al. Competitive and cooperative particle swarm optimization with information sharing mech-anism for global optimization problems[J]. Information Scien-ces, 2015, 293(3): 370-382.
[23] Lynn N, Suganthan P N. Heterogeneous comprehensive lea-rning partile swarm optimization with enhanced exploration and exploitation[J]. Swarm and Evolutionary Computation, 2015, 24: 11-24.
[24] Gong Y J, Li J J, Zhou Y C, et al. Genetic learning particle swarm optimization[J]. IEEE Transactions on Cybernetics, 2016, 46(10): 2277-2290.
[25] Lynn N, Suganthan P N. Ensemble particle swarm optimizer[J]. Applied Soft Computing, 2017, 55: 533-548.
[26] Wang Y, Cai Z Z, Zhang Q F. Differential evolution with composite trial vector generation strategies and control parameters[J]. IEEE Transactions on Evolutionary Computation, 2011, 15(1): 55-66.
[27] Elsayed S M, Sarker R A, Essam D L. A genetic algorithm for solving the CEC'2013 competition problems on real-parameter optimization[C]//Proceedings of the 2013 IEEE Congress on Evolutionary Computation. Piscataway: IEEE, 2013: 356-360.
[28] Zhou X, Wang H, Wang M, et al. Enhancing the modified artificial bee colony algorithm with neighborhood search [J]. Soft Computing, 2017, 21(10): 2733-2743. |