|
[1]Ashkan, M. J., Gargari, E. A. and Lucas, C., Vehicle Fuzzy Controller Design Using Imperialist Competitive Algorithm, Second First Iranian Joint Congress on Fuzzy and Intelligent Systems, Tehran, Iran, 2008.
[2]Abdechiri, M., Faez, K. and Bahrami, H., Adaptive Imperialist Competitive Algorithm (AICA), 2010 9th IEEE International Conference on Cognitive Informatics (ICCI), pp. 940-945, 2010.
[3] Arthur, D. and Vassilvitskii, S., K-means++: The Advantages of Careful Seeding, Proceeding SODA ’07 Proceedings of the eighteenth annual ACM-SIAM Symposium on Discrete Algorithms, pp. 1027-1035, 2007.
[4]Bahrami, H., Faez, K. and Abdechiri, M., Imperialist Competitive Algorithm Using Chaos Theory for Optimization (CICA), 2010 12th International Conference on Computer Modeling and Simulation, pp. 98-103, 2010.
[5]Bergh, F. V. D. and Engelbrecht, A. P., A Cooperative Approach to Particle Swarm Optimization, IEEE Transactions on Evolutionary Computation, 8 (3), 2004.
[6]Chen, R. M., Lo, S. T., Wu, C. L. and Lin, T. H., An Effective Ant Colony Optimization – Based Algorithm for Flow Shop Scheduling, IEEE Conference on Soft Computing in Industrial Applications, pp. 101-106, 2008.
[7]Dorigo, M., Birattari, M. and Stutzle, T., Ant Colony Optimization, IEEE Computational Intelligence Magazine, 1 (4), pp.28-39, 2006.
[8]Das, S., Abraham, A. and Konar, A., Differential Evolution Algorithm: Foundations and Perspectives, Studies in Computational Intelligence, 178, pp. 63-110, 2009.
[9]Elbeltagi, E., Hegazy, T. and Grierson, D., Comparison Among Five Evolutionary-Based Optimization Algortihms, 19, pp. 43-53, 2005.
[10]Herrera, F., Lozano, M. and Sanchez, A. M., A Taxonomy for the Crossover Operator for Real-Coded Genetic Algorithms: An Experimental Study, International Journal of Intelligent Systems, 18, pp. 309-338, 2003.
[11]Lu, L., Luo, Q., Liu, J. Y. and Long, C., An Improved Particle Swarm Optimization Algorithm, Algorithm Granular Computing 2008 IEEE International Conference, pp. 486-490, 2008.
[12]Gargari, E. A. and Lucas, C., Imperialist Competitive Algorithm: An Algorithm for Optimization Inspired by Imperialistic Competition, IEEE Congress on Evolutionary Computation (CEC), pp. 4661-4667, 2007.
[13]Gargari, E. A., Hashemzadeh, F., Rajabioun, R. and Lucas, C., Colonial Competitive Algorithm: A Novel Approach for PID Controller Design in MIMO Distillation Column Process, International Journal of Intelligent Computing and Cybernetics, 1 (3), pp.337-355, 2008.
[14]Goldberg, D. E. and Holland, J. H., Genetic Algorithms and Machine Learning, Machine Learning, 3 (2-3), pp. 95-99, 1988.
[15]Holland, J. H., Adaptation in Natural and Artificial Systems, MIT press, 1992.
[16]Kennedy, J. and Eberhart, R., Particle Swarm Optimization, IEEE International Conference on Neural Networks 1995 Proceedings, 4, pp. 1942-1948, 1995.
[17]Krink, T., Vesterstrom, J. S. and Riget, J., Particle Swarm Optimization with Spatial Particle Extension, Proceedings of the 2002 Congress on Evolutionary Computation, pp. 1474-1479, 2002.
[18]Khorani, A.V., Razavi, B. F. and Ghoncheh, C. A., A new Hybrid Evolutionary Algorithm Based on ICA and GA: Recursive-ICA-GA, The 2010 International Conference on Artificial Intelligence, pp. 131-140, 2010.
[19]Morteza, B., Farshid, J. H. and Hamid, S. S., Metaheuristic Algorithms for Optimization of Regulator Parameters in the Variable Speed DC Motor Drives, 2010 1st Power Electronic & Drive Systems & Technologies Conference (PEDSTC), pp. 230-234, 2010.
[20]Mitchell, M., An Introduction to Genetic Algorithms, MIT press, 1992..
[21]Ong, Y. S. and Keane, A. J., Meta-Lamarckian Learning in Memetic Algorithms, IEEE Transactions on Evolutionary Computation, 8 (2), pp. 99-110, 2004.
[22]Poli, R., Kennedy, J. and Blackwell, T., Particle Swarm Optimization An Overview, Swarm Intelligence, 1 (1), pp. 33-57, 2007.
[23]Shi, Y. and Eberhart, R. C., Empirical Study of Particle Swarm Optimization, Proceedings of the 1999 Congress on Evolutionary Computation (CEC’99), 1999.
[24]Suganthan, P. N., Particle Swarm Optimiser with Neighbourhood Operator, Proceedings of the 1999 Congress on Evolutionary Computation (CEC’99), 1999.
[25]Storn, R. and Price, K., Differential Evolution-A Simple and Efficient Heuristic for Global Optimization over Continuous Space, Journal of Global Optimization, 11 (4), pp. 341-359, 1997.
[26]Ursem, K. R., Diversity-Guided Evolutionary Algorithms, Parallel Problem Solving from Nature-PPSN VII, pp. 462-471, 2002.
[27]William, J. D. and Jackson, J. S., The Essential World History 6th Ed., Cengage Learning, 2010. [28]Whitley, D., Gordon, V. S. and Mathias, K., Lamarckian Evolution, The Baldwin Effect and Function Optimization, Parallel Problem Solving from Nature-PPSN III, pp. 5-15, 1994. [29]Xie, X. F., Zhang, W. J. and Yang, Z. L., A Dissipative Particle Swarm Optimization, Proceedings of the 2002 Congress on Evolutionary Computation (CEC‘02), 1456-1461, 2002.
[30]Yan, T. S., An Improved Genetic Algorithm and Its Blending Application with Neural Network, 2010 2nd International Workshop on Intelligent Systems and Applications(ISA), pp. 1-4, 2010.
[31]Yang, B., Chen, Y. and Zhao, Z., Survey on Applications of Particle Swarm Optimization in Electric Power Systems, IEEE International Conference on Control and Automation (ICCA 2007), pp. 481-486, 2007.
|