How to cite this paper
pirzadeh, Y., shahrabi, J & taghavifard, M. (2012). Rapid Ant based clustering-genetic algorithm (RAC-GA) with local search for clustering problem.International Journal of Industrial Engineering Computations , 3(3), 435-444.
Refrences
Zhang, C., Ouyang, D., & Ning, J. (2010). An artificial bee colony approach for clustering. Expert Systems with Applications, 37(7), 4761-4767.
Larose, D. T. (2005). Discovering Knowledge in Data. A John Wiley & Sons, Inc.
Lumer, E.D., & Faieta, B. (1994). From Animals to Animats3. In: D. Cliff, P.Husbands, J.A. Meyer, W.Stewart (Eds.). MIT Press, Cambridge, MA, 501–508.
Deneubourg, J.L., Goss, S., Franks, N., Sendova-Franks, A., Detrain, C., & Chretien, L. (1991). From Animals to Animats1.In: J.A. Meyer et, S.W.Wilson (Eds.), MIT Press, Cambridge, MA, 356–363.
Kennedy, J., & Eberhart, R. (1999). Particle swarm optimization. In: Proceedings of theIEEE International Conference on Neural Networks, Piscataway, NJ., 1942–1948.
Krishna, K., & Murty. (1999). Genetic K-means Algorithm. IEEE Transactions on Systems Man and Cybernetics B Cybernetics, 29, 433–439.
Kao, Y.T., Zahara, E., & Kao, I.W. (2008).A hybridized approach to data clustering. Expert Systems with Applications, 34(3), 1754-1762.
Dorigo, M. (1991). Optimization learning and natural algorithms. (in italian) Ph.D thesis.
Mualik, U., & Bandyopadhyay, S. (2002). Genetic algorithm based clustering technique. Pattern Recognition, 33(9), 1455–1465.
Kuntz, P., Layzell,P., & Snyers, D. (1998) a stochastic heuristic for visualizing graph. Clusters in a bi-dimensional space prior to partitioning. Journal of Heuristics, 5(3), 327–351.
Shelokar, P.S., Jayaraman, V.K., & Kulkarni, B.D. (2004). An ant colony approach for clustering. Analytica Chimica Acta, 509(2), 187–195.
Pirzadeh, Y., Shahrabi, J., & Anvari, M.T. (2011). Rapid Ant clustering Algorithm with multiple evaporation coefficients, the fifth Conference of data mining, Iran.
Xu, R., & Wunsch, D. (2005). Survey of clustering algorithms. IEEE transactions on neural networks, 16(3), 645-678.
Selim, S. Z., & Al Sultan, K.S. (1991). A simulated annealing algorithm for the clustering problem. Pattern Recognition, 24, 1003–1008.
Sung, C. S., & Jin, H. W. (2000). A Tabu-search-based heuristic for clustering. Pattern Recognition, 33, 849–858.
Niknam, T. & Amiri, B. (2010). An efficient hybrid approach based on PSO, ACO and k-means for cluster analysis. Applied soft computing, 10(1), 183-197.
Larose, D. T. (2005). Discovering Knowledge in Data. A John Wiley & Sons, Inc.
Lumer, E.D., & Faieta, B. (1994). From Animals to Animats3. In: D. Cliff, P.Husbands, J.A. Meyer, W.Stewart (Eds.). MIT Press, Cambridge, MA, 501–508.
Deneubourg, J.L., Goss, S., Franks, N., Sendova-Franks, A., Detrain, C., & Chretien, L. (1991). From Animals to Animats1.In: J.A. Meyer et, S.W.Wilson (Eds.), MIT Press, Cambridge, MA, 356–363.
Kennedy, J., & Eberhart, R. (1999). Particle swarm optimization. In: Proceedings of theIEEE International Conference on Neural Networks, Piscataway, NJ., 1942–1948.
Krishna, K., & Murty. (1999). Genetic K-means Algorithm. IEEE Transactions on Systems Man and Cybernetics B Cybernetics, 29, 433–439.
Kao, Y.T., Zahara, E., & Kao, I.W. (2008).A hybridized approach to data clustering. Expert Systems with Applications, 34(3), 1754-1762.
Dorigo, M. (1991). Optimization learning and natural algorithms. (in italian) Ph.D thesis.
Mualik, U., & Bandyopadhyay, S. (2002). Genetic algorithm based clustering technique. Pattern Recognition, 33(9), 1455–1465.
Kuntz, P., Layzell,P., & Snyers, D. (1998) a stochastic heuristic for visualizing graph. Clusters in a bi-dimensional space prior to partitioning. Journal of Heuristics, 5(3), 327–351.
Shelokar, P.S., Jayaraman, V.K., & Kulkarni, B.D. (2004). An ant colony approach for clustering. Analytica Chimica Acta, 509(2), 187–195.
Pirzadeh, Y., Shahrabi, J., & Anvari, M.T. (2011). Rapid Ant clustering Algorithm with multiple evaporation coefficients, the fifth Conference of data mining, Iran.
Xu, R., & Wunsch, D. (2005). Survey of clustering algorithms. IEEE transactions on neural networks, 16(3), 645-678.
Selim, S. Z., & Al Sultan, K.S. (1991). A simulated annealing algorithm for the clustering problem. Pattern Recognition, 24, 1003–1008.
Sung, C. S., & Jin, H. W. (2000). A Tabu-search-based heuristic for clustering. Pattern Recognition, 33, 849–858.
Niknam, T. & Amiri, B. (2010). An efficient hybrid approach based on PSO, ACO and k-means for cluster analysis. Applied soft computing, 10(1), 183-197.