References
- [1] Gerardo Beni and Jing Wang, Swarm intelligence in cellular robotic systems, In Robots and Biological Systems: Towards a New Bionics? Springer, 1993, pp. 703–71210.1007/978-3-642-58069-7_38
- [2] J.M. Bishop, Stochastic searching networks, In IEEE Conf. on Artificial Neural Networks, 1989, IEEE, pp. 329–331
- [3] Daniel Bratton and James Kennedy, Defining a standard for particle swarm optimization, In Swarm Intelligence Symposium, 2007, IEEE, pp. 120–12710.1109/SIS.2007.368035
- [4] Ran Cheng and Yaochu Jin, A competitive swarm optimizer for large scale optimization, Cybernetics, IEEE Transactions on, vol. 45, 2015, pp. 191–20410.1109/TCYB.2014.232260224860047
- [5] Shi Cheng, Yuhui Shi, Quande Qin, TO Ting, and Ruibin Bai, Maintaining population diversity in brain storm optimization algorithm, In Evolutionary Computation, 2014, IEEE, pp. 3230–323710.1109/CEC.2014.6900255
- [6] Shi Cheng, Yuhui Shi, Quande Qin, Qingyu Zhang, and Ruibin Bai, Population diversity maintenance in brain storm optimization algorithm, Journal of Artificial Intelligence and Soft Computing Research, vol. 4, 2014, pp. 83–9710.1515/jaiscr-2015-0001
- [7] Maurice Clerc and James Kennedy, The particle swarm-explosion, stability, and convergence in a multidimensional complex space, Evolutionary Computation, IEEE Tansaction on Evolutionary Computation, vol. 6, 2002, pp. 58–7310.1109/4235.985692
- [8] Swagatam Das, Arijit Biswas, Sambarta Dasgupta, and Ajith Abraham, Bacterial foraging optimization algorithm: theoretical foundations, analysis, and applications, In Foundations of Computational Intelligence Volume 3, Springer, 2009, pp. 23–5510.1007/978-3-642-01085-9_2
- [9] Marco Dorigo, Vittorio Maniezzo, and Alberto Colorni, Ant system: optimization by a colony of cooperating agents, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 26, 1996, pp. 29–4110.1109/3477.48443618263004
- [10] R C Eberhart and J Kennedy, A new optimizer using particle swarm theory, Proceedings of the Sixth International Symposium on Micro Machine and Human Science, 1995, pp. 39–43
- [11] Amir Hossein Gandomi and Amir Hossein Alavi, Krill herd: a new bio-inspired optimization algorithm, Communications in Nonlinear Science and Numerical Simulation, vol. 17, 2012, pp. 4831–484510.1016/j.cnsns.2012.05.010
- [12] Dervis Karaboga and Bahriye Basturk, A powerful and efficient algorithm for numerical function optimization: artificial bee colony (abc) algorithm, Journal of global optimization, vol. 39, 2007, pp. 459–47110.1007/s10898-007-9149-x
- [13] James Kenndy and R C Eberhart, Particle swarm optimization, In IEEE International Conference on Neural Networks, 1995, IEEE, pp. 1942–1948
- [14] James Kennedy, The behavior of particles, In Evolutionary Programming VII, 1998, Springer, pp. 579–58910.1007/BFb0040809
- [15] James Kennedy, Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance, In Proceedings of the 1999 Congress on Evolutionary Computation, 1999, IEEE, pp. 1931–1938
- [16] James Kennedy, Particle swarm optimization, In Encyclopedia of Machine Learning, Springer, 2010, pp. 760–766
- [17] James Kennedy, James F Kennedy, and Russell C Eberhart, Swarm intelligence, Morgan Kaufmann, 2001
- [18] James Kennedy and Rui Mendes, Population structure and particle swarm performance, In Congress on Evolutionary Computation, 2002, IEEE computer Society
- [19] James Kennedy and Rui Mendes, Neighborhood topologies in fully informed and best-of-neighborhood particle swarms, IEEE Transactions on Systems Man and Cybernetics Part C Applications and Reviews, vol. 36, 2006, p. 51510.1109/TSMCC.2006.875410
- [20] Dong Hwa Kim, Ajith Abraham, and Jae Hoon Cho, A hybrid genetic algorithm and bacterial foraging approach for global optimization, Information Sciences, vol. 177, 2007, pp. 3918–393710.1016/j.ins.2007.04.002
- [21] KN Krishnanand and D Ghose, Glowworm swarm optimisation: a new method for optimising multimodal functions, International Journal of Computational Intelligence Studies, vol. 1, 2009, pp. 93–11910.1504/IJCISTUDIES.2009.025340
- [22] KN Krishnanand and Debasish Ghose, Glowworm swarm optimization for simultaneous capture of multiple local optima of multimodal functions, Swarm intelligence, vol. 3, 2009, pp. 87–12410.1007/s11721-008-0021-5
- [23] Xiaolei Li, A new intelligent optimization-artificial fish swarm algorithm, Doctor thesis, 2003
- [24] Seyedali Mirjalili, Seyed Mohammad Mirjalili, and Andrew Lewis, Grey wolf optimizer, Adv. Eng. Softw., vol. 69, March 2014, pp. 46–6110.1016/j.advengsoft.2013.12.007
- [25] S.J. Nasuto and J.M. Bishop, Convergence analysis of stochastic diffusion search, Journal of Parallel Algorithms and Applications, vol. 14, 1999, pp. 89–10710.1080/10637199808947380
- [26] Pedro C Pinto, Thomas A Runkler, and Joao MC Sousa, Wasp swarm algorithm for dynamic max-sat problems, In Adaptive and Natural Computing Algorithms, Springer, 2007, pp. 350–35710.1007/978-3-540-71618-1_39
- [27] Esmat Rashedi, Hossein Nezamabadi-Pour, and Saeid Saryazdi, Gsa: a gravitational search algorithm, Information sciences, vol. 179, 2009, pp. 2232–224810.1016/j.ins.2009.03.004
- [28] Yuhui Shi, Brain storm optimization algorithm, In Advances in Swarm Intelligence, Springer, 2011, pp. 303–30910.1007/978-3-642-21515-5_36
- [29] Yuhui Shi and Russell Eberhart, A modified particle swarm optimizer, In Evolutionary Computation, 1998, IEEE, pp. 69–73
- [30] Yang Shiqin, Jiang Jianjun, and Yan Guangxing, A dolphin partner optimization, In Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01, GCIS ’09, 2009, pp. 124–12810.1109/GCIS.2009.464
- [31] Arlindo Silva, Ana Neves, and Ernesto Costa, Chasing the swarm: a predator prey approach to function optimisation, In Proceedings of the MENDEL2002—-8th International Conference on Soft Computing, Brno, Czech Republic, 2002
- [32] Ying Tan and Yuanchun Zhu, Fireworks algorithm for optimization, In Advances in Swarm Intelligence, Springer, 2010, pp. 355–36410.1007/978-3-642-13495-1_44
- [33] Shiqin Yang and Yuji Sato, Fitness predator optimizer to avoid premature convergence for multimodal problems, In Systems, Man and Cybernetics, 2014 IEEE International Conference on, 2014, IEEE, pp. 258–26310.1109/SMC.2014.6973917
- [34] Xin-She Yang, Nature-inspired metaheuristic algorithms, Luniver press, 2010
- [35] Xin-She Yang, A new metaheuristic bat-inspired algorithm, In Nature inspired cooperative strategies for optimization (NICSO 2010), Springer, 2010, pp. 65–7410.1007/978-3-642-12538-6_6
- [36] Xin-She Yang and Suash Deb, Cuckoo search via lévy flights, In World Congress on Nature & Biologically Inspired Computing, NaBIC, 2009, IEEE, pp. 210–21410.1109/NABIC.2009.5393690
- [37] You Zhou and Ying Tan, Gpu-based parallel particle swarm optimization, In Evolutionary Computation, 2009, CEC’09, IEEE Congress on, 2009, IEEE, pp. 1493–150010.1109/CEC.2009.4983119