|| I. Mukherjee and P. K. Ray, “A review of optimization techniques in metal cutting processes,” Computers & Industrial Engineering, Vol. 50, no.1-2, pp.15-34, 2006.|
 M. Imiela, “High-ﬁdelity optimization framework for helicopter rotors,” Aerospace Science and Technology, 2011.
 I. Averbakh, “Computing and minimizing the relative regret in combinatorial optimization with interval data,” Discrete Optimization, Vol. 2, no.4, pp.273-287, 2004.
 B. Srinivasan, D. Bonvin, E. Visser and S. Palanki, “Dynamic optimization of batch processes II. Role of measurements in handling uncertainty,” Computers and Chemical Engineering, Vol. 27, no.1, pp. 27-44, 2002.
 B. Y. Mirghani, K. G. Mahinthakumar, M. E. Tryby, R. S. Ranjithan and E. M. Zechman,“A parallel evolutionary strategy based simulation–optimization approach for solving groundwater source identiﬁcation problems,” Advances in Water Resources, Vol. 32, no. 9, pp. 1373-1385, 2009.
 I. Ioslovich and P. Gutman,“Optimal control of crop spacing in a plant factory,” Automatica, Vol. 36, no. 11, pp.1665-1668, 2000.
 E. Amaldi, A. Capone, M. Cesana, I. Filippini and F. Malucelli “Optimization models and methods for planning wireless mesh networks,” Computer Networks, Vol. 52, no.11, pp. 2159-2171, 2008.
 A. Khetrapal：Ant Based Distributed certificate revocation in vehicular ad hoc networks. 取自：http://www.ankurkhetrapal.com/research/proteus.htm
 M. Dorigo, M. Birattari, and T. Stutzle, “Ant Colony Optimization,” IEEE computation intelligence magazine, Vol. 1, no. 4, pp. 28-39, 2006.
 D. Karaboga,“An idea based on honey bee swarm for numerical optimization,” technical report-tr06, 2005. 取自：http://www-lia.deis.unibo.it/Courses/SistInt/articoli/bee-colony1.pdf
 S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach (Third edition), 2011.
 J. Kennedy and R. C. Eberhart, “Particle swarm optimization,” In Proceedings of IEEE Conference on Neural Networks, Vol. 4, pp. 1942-1948, 1995.
 N. M. Kwok, Q. P. Ha, Dikai Liu, and Gu Fang, “Contrast Enhancement and Intensity Preservation for Gray-Level Images Using Multi-objective Particle Swarm Optimization,” IEEE transaction on automation science and engineering, vol. 6, no. 1, pp.145-155, 2009.
 J. F. Wang, W.H. Li, “Based on Extended T-S Fuzzy Model of Self-adaptive Disturbed PSO Algorithm,” Second International Conference on Information and Computing Science, Vol. 3, pp.153-155, 2009.
 W. Liu, B. Gao and X. Liang, “Power System Reactive Power Optimization Based on Improved PSO,” World Congress on Intelligent Control and Automation, pp. 3974-3979, 2010
 M. Cui and S. Hu, ”Search engine optimization research for website promotion,” International Conference on Information Technology, Computer Engineering and Management Sciences. Vol.4, pp.100-103, 2011.
 Y. T. Hsiao, C. L. Chuang, J. A. Jiang and C. C. Chien, “A Novel Optimization Algorithm : Space Gravitational Optimization,” International Conference on Systems, Man and Cybernetics, Vol. 3, pp. 2323-2328, 2005.
 G, Renner, A. Ekart, “Genetic algorithms in computer aided design,” Computer-Aided Design, Vol. 117, no. 1-2, pp. 216-221, 2002.
 J. E. B Easley and R. C. Chu, “A genetic algorithm for the set covering problem,” European Journal of Operational Research, Vol. 94, no. 2, pp. 392-404, 1995.
 T. K.n Liu, C. H. Chen and J. H. Chou, “Optimization of short-haul aircraft schedule recovery problems using a hybrid multiobjective genetic algorithm,” Expert Systems with Applications, Vol. 37, no. 3 pp. 2307-2315, 2010.
 Z. H. Zhou, Y. Jiang, Y. B. Yang and S. F. Chen, “Lung cancer cell identification based on artificial neural network ensembles,” Artificial intelligence in medicine, Vol. 24, no. 1, pp. 25-26, 2002
 E. Lewis, C. Sheridan, M. O’Farrell, D. King, C. Flanagan, W. B. Lyons, C. Fitzpatrick, “Principal component analysis and artiﬁcial neural network based approach to analysing optical ﬁbre sensors signals,” Sensors and Actuators, Vol. 136, no. 1, pp. 28-38, 2007
 H. B. Bahar and D. H. Horrocks “Dynamic weight estimation using an artificial neural network,” Artificial intelligence in Engineering, Vol. 12, no. 1-2, pp. 135-139, 1998.
 A. RajaRajan, “Brain Disorder Detection using Artificial Neural Network”, 3rd International Conference on Electronics Computer Technology (ICECT), Vol. 4, pp. 268-272, 2011.
 Y. Shi, H. c. Liu, L. Gao and G. Zhang, “Cellular particle swarm optimization,” Information Sciences, Vol. 181, no. 20, pp. 4460-4493, 2007.
 J. Jie, J. Zeng, C. Han and Q. Wang, “Knowledge-based cooperative particle swarm optimization,” Applied Mathematics and Computation, 2008.
 S.Z. Zhao, P.N. Suganthan, Q. K. Pan and M. F. Tasgetiren “Dynamic multi-swarm particle swarm optimizer with harmony search,” Expert Systems with Applications, Vol. 605, no. 2, pp. 861-873, 2011.
 Y. Wang, B. Li, T. Weise, J. Wang, B. Yuan and Q. Tian “Self-adaptive learning based particle swarm optimization,” Information Sciences, Vol. 181, no. 20, pp. 4515-4538, 2011.
 D. Jia, G. Zheng, B. Qu and M. K. Khan, “A hybrid particle swarm optimization algorithm for high-dimensional problems,” Computers & Industrial Engineering, Vol. 41, no. 4, pp. 1117-1122, 2011.
 M. S. Arumugam, M.V.C. Rao and A. W.C. Tan, “A novel and effective particle swarm optimization like algorithm with extrapolation technique,” Applied Soft Computing, Vol. 9, no. 1, pp. 308-320, 2009.
 W. D. Chang and S. P. Shih, “PID controller design of nonlinear systems using an improved particle swarm optimization approach,” Commun Nonlinear Sci Numer Simulat, Vol. 15, no.11, pp.3632-3639. 2010.
 J. J. Liang and P. N. Suganthan, “Dynamic Multi-Swarm Particle Swarm Optimizer,” Swarm Intelligence Symposium, pp. 124-129, 2005.
 L. Lu, Q. Luo, J. Y. Liu and C. Long, “An Improved Particle Swarm Optimization Algorithm,” IEEE International Conference on Granular Computing, Vol. 1, pp. 585-589, 2008.
 G. Y. Wang and D. X. Han, “Particle Swarm Optimization Based on Self-adaptive Acceleration Factors,” WGEC ’’09. 3rd International Conference on Genetic and Evolutionary Computing, pp. 637-640 ,2009.
 P. K. Tripathi, S. Bandyopadhyay and S. K. Pal “Multi-Objective Particle Swarm Optimization with time variant inertia and acceleration coeﬃcients,” Information Sciences, Vol. 177, no. 22, pp. 5033-5049, 2007.
 R.C. Eberhart and Y. Shi, “Tracking and Optimizing Dynamic Systems with Particle Swarms,” Proceedings Congress on Evolutionary Computation, Vol. 1, no. 22, pp. 94-100, 2001..
 Y. Liu, Z. Qin, Z. Shi and J. Lu, “Center particle swarm optimization,” Neurocomputing, Vol. 70, no. 46, pp. 672-6792007.
 N. Higashi and H. Iba, “Particle swarm optimization with Gaussian mutation,” Proceedings of the IEEE Swam Intelligence Symposium, pp. 72-79,2003.
 A. Ratnaweera, S.K. Halgamuge, Watson H.C. , “Self-organizing Hierarchical Particle Swarm Optimizer With Time-Varying Acceleration Coefficient,” IEEE Transactions on Evolutionary Computation, Vol. 8, no. 3, pp.240-255, 2004.
 M. Pant, T. Radha and V.P.Singh, “A new particle swarm optimization with quadratic interpolation,” In Proceedings of IEEE International Conference on Computational Intelligence and Multimedia Applications, Vol. 1, pp. 55–60, 2007.
 N. Iwasaki, K. Yasuda, G. Ueno, “Dynamic parameter tuning of particle swarm optimization,” IEEJ Transactions on Electrical and Electronic Engineering 1, Vol. 1, no. 4, pp. 353-363, 2006.
 J. J. Liang, P. N. Suganthan, and K. Deb, “Novel composition test functions for numerical global optimization,” In Proceedings of IEEE on Swarm Intelligence Symposium, pp. 68-75, 2005.
 P. N. Suganthan, N. Hansen, J. J. Liang, K. Deb, Y. -P. Chen, A. Auger & S. Tiwari, “Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization,” Technical report of Nanyang Technological University, 2005. 取自：http://www.lri.fr/~hansen/Tech-Report-May-30-05.pdf。
 K. Tang, X. Lǐ, P. N. Suganthan, Z. Yang, and T. Weise: “Benchmark Functions for the CEC’’2010 Special Session and Competition on Large-Scale Global Optimization,” University of Science and Technology of China (USTC) and Nature Inspired Computation and Applications Laboratory (NICAL), 2010. 取自：http://nical.ustc.edu.cn/cec10ss.php。
 R. Salomon, ”Reevaluating genetic algorithm performance under coordinate rotation of benchmark functions,” BioSystems, Vol. 39, no. 3, pp. 263-278, 1996.
 G. Nicosia, S. Rinaudo and E. Sciacca, “An evolutionary algorithm-based approach to robust analog circuit design using constrained multi-objective optimization,” Knowledge-Based Systems, Vol. 21, no. 3, pp. 175-183, 2008.
 H. Fang, L. Chen and Zuyi Shen, “Application of an improved PSO algorithm to optimal tuning of PID gains for water turbine governor,” Energy Conversion and Management, Vol. 52, no. 4, pp.1763-1770, 2011.
 H Fang, L Chen, N Dlakavu and Z Shen, “Basic modeling and simulation tool for analysis of hydraulic transients in hydroelectric power plants,” IEEE Trans Energy Convers, Vol. 23, no. 3, pp.834-841,2008.
 C. Jiang, Y. Ma and C. Wang, “PID controller parameters optimization of hydro-turbine governing systems using deterministic-chaotic-mutation evolutionary programming(DCMEP),” Energy Convers Manage, Vol. 47, no. 9-10, pp.1222-1230, 2009.
 J. Fang, D. Zheng and Z. Ren, “Computation of stabilizing PI and PID controllers by using Kronecker summation method,” Energy Convers Manage, Vol.50, no. 7, pp.1821-1827, 2009.
 A. Bartoszewicz and N. Leverton, “ITAE optimal sliding modes for thirdorder systems with input signal and state constraints,” IEEE Trans Autom Contr, Vol. 50, no. 8, pp.1928–1932, 2010.