Abstract
In this paper we improve the meta heuristic algorithm known as Cuckoo Search (CS) to solve optimization problems. The proposed Inter-species Cuckoo Search (ISCS) algorithm is based on the brood parasitic behavior of different inter-related cuckoo species in different areas in combination with Levy flight behavior(which changes with the terrain) of birds. The proposed algorithm is then tested against various test functions and its performance is compared with genetic algorithms, particle swarm optimization and previous versions of Cuckoo Search algorithm.
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References
Yang, X.-S., Deb, S.: Engineering Optimisation by Cuckoo Search. Int. J. Mathematical Modelling and Numerical Optimisation 1(4), 330–343 (2010)
Yang, X.S., Deb, S.: Engineering Optimisation by Cuckoo Search. Int. J. of Mathematical Modelling and Numerical Optimisation 1(4), 330–343 (2010)
Yang, X.-S.: A New Metaheuristic Bat-Inspired Algorithm. In: González, J.R., Pelta, D.A., Cruz, C., Terrazas, G., Krasnogor, N. (eds.) NICSO 2010. SCI, vol. 284, pp. 65–74. Springer, Heidelberg (2010)
Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press (1999)
Deb, K.: Optimisation for Engineering Design. Prentice-Hall, New Delhi (1995)
Yang, X.S.: Nature-Inspired Metaheuristic Algorithms. Luniver Press (2008)
Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: Overview and conceptural comparision. ACM Comput. Surv. 35, 268–308 (2003)
Yang, X.S.: Biology-derived algorithms in engineering optimizaton. In: Olarius, Zomaya (eds.) Handbook of Bioinspired Algorithms and Applications, ch.32. Chapman & Hall / CRC
Kennedy, J., Eberhart, R., Shi, Y.: Swarm intelligence. Academic Press (2001)
Payne, R.B., Sorenson, M.D., Klitz, K.: The Cuckoos. Oxford University Press (2005)
Brown, C., Liebovitch, L.S., Glendon, R.: Lévy flights in Dobe Ju/’hoansi foraging patterns. Human Ecol. 35, 129–138 (2007)
Pavlyukevich, I.: Lévy flights, non-local search and simulated annealing. J. Computational Physics 226, 1830–1844 (2007)
Pavlyukevich, I.: Cooling down Lévy flights. J. Phys. A: Math. Theor. 40, 12299–12313 (2007)
Reynolds, A.M., Frye, M.A.: Free-flight odor tracking in Drosophila is consistent with an optimal intermittent scale-free search. PLoS One 2, e354 (2007)
Shlesinger, M.F., Zaslavsky, G.M., Frisch, U. (eds.): Lévy Flights and Related Topics in Phyics. Springer (1995)
Shlesinger, M.F.: Search research. Nature 443, 281–282 (2006)
Chattopadhyay, R.: A study of test functions for optimization algorithms. J. Opt. Theory Appl. 8, 231–236 (1971)
Schoen, F.: A wide class of test functions for global optimization. J. Global Optimization 3, 133–137 (1993)
Shang, Y.W., Qiu, Y.H.: A note on the extended rosenrbock function. Evolutionary Computation 14, 119–126 (2006)
Hartigan, J.A., Wong, M.A.: Algorithm AS 136: A K-Means Clustering Algorithm. Journal of the Royal Statistical Society, Series C (Applied Statistics) 28(1), 100–108 (1979)
Ding, C., He, X.: K-means Clustering via Principal Component Analysis. In: Proc. of Int’l Conf. Machine Learning (ICML), pp. 225–232 (July 2004)
Winkel, M.: Introduction to Lévy processes. pp. 15–16 (retrieved January 07, 2013)
Alamgir, M., von Luxburg, U.: Multi-agent random walks for local clustering on graphs. In: IEEE 10th International Conference on Data Mining (ICDM), pp. 18–27 (2010)
Sijbers, J., den Dekker, A.J., Raman, E., Van Dyck, D.: Parameter estimation from magnitude MR images. International Journal of Imaging Systems and Technology 10(2), 109–114 (1999)
Srivastava, P.R., Varshney, A., Nama, P., Yang, X.S.: Software test effort estimation: a model based on cuckoo search. International Journal of Bio-inspired Computation 4(5), 278–285 (2012)
Marichelvam, M.K.: An improved hybrid Cuckoo Search (IHCS) metaheuristics algorithm for permutation flow shop scheduling problems. International Journal of Bio-inspired Computation 4(4), 200–205 (2012)
Gherboudj, A., Layeb, A., Chikhi, S.: Solving 0-1 knapsack problems by a discrete binary version of cuckoo search algorithm. International Journal of Bio-inspired Computation 4(4), 229–236 (2012)
Swagatam, D., Suganthan, P.N.: Criteria for CEC 2011 Competition on Testing Evolutionary Algorithms on Real World Optimization Problems. Technical Report (December 2010)
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Das, S., Dasgupta, P., Panigrahi, B.K. (2013). Inter-species Cuckoo Search via Different Levy Flights. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2013. Lecture Notes in Computer Science, vol 8297. Springer, Cham. https://doi.org/10.1007/978-3-319-03753-0_46
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DOI: https://doi.org/10.1007/978-3-319-03753-0_46
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