An Improved Imperialist Competitive Algorithm based on a new assimilation strategy
Subject Areas : Evolutionary Computing
1 - Department of Computer Engineering, Safashahr Branch, Islamic Azad University, Safashahr, Iran
Keywords:
Abstract :
[1] Talatahari, S., Farahmand Azar, B., Sheikholeslami, R., & Gandomi, A. H. (2012). Imperialist competitive algorithm combined with chaos for global optimization. Communications in Nonlinear Science and Numerical Simulation, 17(3), 1312-1319. doi:10.1016/j.cnsns.2011.08.021
[2] Holland, J. H. (1975). Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence. U Michigan Press.
[3] Kennedy, J., & Eberhart, R. (1995, November). Particle swarm optimization. In Proceedings of IEEE international conference on neural networks (Vol. 4, No. 2, pp. 1942-1948).
[4] Dorigo, M., & Gambardella, L. M. (1997). Ant colony system: a cooperative learning approach to the traveling salesman problem. Evolutionary Computation, IEEE Transactions on, 1(1), 53-66.
[5] Storn, R., & Price, K. (1995). Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces. Berkeley: ICSI.
[6] Webster, B., & Bernhard, P. J. (2003). A local search optimization algorithm based on natural principles of gravitation. http://hdl.handle.net/11141/117
[7] Yang, X. S. (2009). Firefly algorithms for multimodal optimization. In Stochastic algorithms: foundations and applications (pp. 169-178). Springer Berlin Heidelberg. doi : 10.1007/978-3-642-04944-6_14
[8] Atashpaz-Gargari, E., & Lucas, C. (2007, September). Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition. In Evolutionary Computation, 2007. CEC 2007. IEEE Congress on (pp. 4661-4667). IEEE. doi : 10.1109/CEC.2007.4425083
[9] Kaveh, A. (2014). Advances in Metaheuristic Algorithms for Optimal Design of Structures.(page 349-355, ch 11) Springer International Pu. doi: 10.1007/978-3-319-05549-7
[10] Esmaeilzadeh, M. (2013). A modified colonial competitive algorithm for optimizing convex functions. International Journal of Intelligent Computing and Cybernetics, 6(4), 370-385. doi : 10.1108/IJICC-02-2013-0006
[11] Atashpaz-Gargari, E., Hashemzadeh, F., & Lucas, C. (2008, June). Designing MIMO PID controller using colonial competitive algorithm: applied to distillation column process. In Evolutionary Computation, 2008. CEC 2008.(IEEE World Congress on Computational Intelligence). IEEE Congress on (pp. 1929-1934). IEEE. doi: 10.1109/CEC.2008.4631052
[12] Nemati, K., Shamsuddin, S. M., & Darus, M. (2014). An optimization technique based on imperialist competition algorithm to measurement of error for solving initial and boundary value problems. Measurement, 48, 96-108. doi: 10.1016/j.measurement.2013.10.043
[13] Zarandi, M. H., Zarinbal, M., Ghanbari, N., & Turksen, I. B. (2013). A new fuzzy functions model tuned by hybridizing imperialist competitive algorithm and simulated annealing. Application: Stock price prediction. Information Sciences, 222, 213-228. doi: 10.1016/j.ins.2012.08.002
[14] Niknam, T., Taherian Fard, E., Pourjafarian, N., & Rousta, A. (2011). An efficient hybrid algorithm based on modified imperialist competitive algorithm and K-means for data clustering. Engineering Applications of Artificial Intelligence, 24(2), 306-317. doi : 10.1016/j.engappai.2010.10.001
[15] Kayvanfar, V., & Zandieh, M. (2012). The economic lot scheduling problem with deteriorating items and shortage: an imperialist competitive algorithm. The International Journal of Advanced Manufacturing Technology, 62(5-8), 759-773. doi: 10.1007/s00170-011-3820-6
[16] Karimi, N., Zandieh, M., & Najafi, A. A. (2011). Group scheduling in flexible flow shops: a hybridised approach of imperialist competitive algorithm and electromagnetic-like mechanism. International Journal of Production Research, 49(16), 4965-4977. doi : 10.1080/00207543.2010.481644
[17] Mohammadi-ivatloo, B., Rabiee, A., Soroudi, A., & Ehsan, M. (2012). Imperialist competitive algorithm for solving non-convex dynamic economic power dispatch. Energy, 44(1), 228-240. doi : 10.1016/j.energy.2012.06.034
[18] Ahmadi, M. A., Ebadi, M., Shokrollahi, A., & Majidi, S. M. J. (2013). Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir. Applied Soft Computing, 13(2), 1085-1098. doi: 10.1016/j.asoc.2012.10.009
[19] Meysam Mousavi, S., Tavakkoli-Moghaddam, R., Vahdani, B., Hashemi, H., & Sanjari, M. J. (2013). A new support vector model-based imperialist competitive algorithm for time estimation in new product development projects. Robotics and Computer-Integrated Manufacturing, 29(1), 157-168. doi : 10.1016/j.rcim.2012.04.006
[20] Coelho, L. D. S., Afonso, L. D., & Alotto, P. (2012). A modified imperialist competitive algorithm for optimization in electromagnetics. Magnetics, IEEE Transactions on, 48(2), 579-582. doi: 10.1109/TMAG.2011.2172400
[21] Lucas, C., Nasiri-Gheidari, Z., & Tootoonchian, F. (2010). Application of an imperialist competitive algorithm to the design of a linear induction motor. Energy Conversion and Management, 51(7), 1407-1411. doi: 10.1016/j.enconman.2010.01.014
[22] Liu, J. Y. C., Su, C., & Chiu, C. T. (2013, July). On the Convergence of Imperialist Competitive Algorithm. In Modelling Symposium (AMS), 2013 7th Asia (pp. 16-20). IEEE. doi: 10.1109/AMS.2013.9
[23] Xing, B., & Gao, W. J. (2014). Imperialist Competitive Algorithm. In Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms (pp. 203-209). Springer International Publishing. doi: 10.1007/978-3-319-03404-1_15
[24] Afonso, L. D., Mariani, V. C., & Dos Santos Coelho, L. (2013). Modified imperialist competitive algorithm based on attraction and repulsion concepts for reliability-redundancy optimization. Expert Systems with Applications, 40(9), 3794-3802. doi: 10.1016/j.eswa.2012.12.093
[25]Naimi Sadigh, A., Mozafari, M., & Karimi, B. (2012). Manufacturer–retailer supply chain coordination: A bi-level programming approach. Advances in Engineering Software, 45(1), 144-152. doi: 10.1016/j.advengsoft.2011.09.008
[26] Duan, H., Xu, C., Liu, S., & Shao, S. (2010). Template matching using chaotic imperialist competitive algorithm. Pattern recognition letters, 31(13), 1868-1875. doi: 10.1016/j.patrec.2009.12.005
[27] Behnamian, J., & Zandieh, M. (2011). A discrete colonial competitive algorithm for hybrid flowshop scheduling to minimize earliness and quadratic tardiness penalties. Expert Systems with Applications, 38(12), 14490-14498. doi: 10.1016/j.eswa.2011.04.241
[28]Ramezani, F., Lotfi, S., & Soltani-Sarvestani, M. A. (2012). A hybrid evolutionary imperialist competitive algorithm (HEICA). In Intelligent Information and Database Systems (pp. 359-368). Springer Berlin Heidelberg. doi: 10.1007/978-3-642-28487-8_37
[29] Lepagnot, J., Idoumghar, L., & Fodorean, D. (2013, October). Hybrid Imperialist Competitive Algorithm with Simplex Approach: Application to Electric Motor Design. In Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on (pp. 2454-2459). IEEE. doi: 10.1109/SMC.2013.419
[30] Goldansaz, S. M., Jolai, F., & Zahedi Anaraki, A. H. (2013). A hybrid imperialist competitive algorithm for minimizing makespan in a multi-processor open shop. Applied Mathematical Modelling, 37(23), 9603-9616. doi: 10.1016/j.apm.2013.05.002
[31] Jula, A., Othman, Z., & Sundararajan, E. (2013, April). A hybrid imperialist competitive-gravitational attraction search algorithm to optimize cloud service composition. In Memetic Computing (MC), 2013 IEEE Workshop on (pp. 37-43). IEEE. doi : 10.1109/MC.2013.6608205
[32] Yao, X., Liu, Y., & Lin, G. (1999). Evolutionary programming made faster. Evolutionary Computation, IEEE Transactions on, 3(2), 82-102.
[33] Kundu, R., Das, S., Mukherjee, R., & Debchoudhury, S. (2014). An improved particle swarm optimizer with difference mean based perturbation. Neurocomputing, 129, 315-333. doi : 10.1016/j.neucom.2013.09.026
[34] Wilcoxon, F. (1945). Individual comparisons by ranking methods. Biometrics bulletin, 80-83.
[35] Zhang, J., & Sanderson, A. C. (2009). JADE: adaptive differential evolution with optional external archive. Evolutionary Computation, IEEE Transactions on, 13(5), 945-958. doi: 10.1109/TEVC.2009.2014613
[36] Gao, W., & Liu, S. (2011). Improved artificial bee colony algorithm for global optimization. Information Processing Letters, 111(17), 871-882. doi: 10.1016/j.ipl.2011.06.002
[37] Kaveh, A., & Talatahari, S. (2010). Optimum design of skeletal structures using imperialist competitive algorithm. Computers & structures, 88(21), 1220-1229.
[38] Xu, J., He, H., & Man, H. (2012). DCPE co-training for classification. Neurocomputing, 86, 75-85.
[39] Xu, J., & Man, H. (2011). Dictionary learning based on laplacian score in sparse coding. In Machine Learning and Data Mining in Pattern Recognition (pp. 253-264). Springer Berlin Heidelberg.
