Abstract
Due to interference phenomena among constrained dimensions of the multimodal optimization or complex constrained optimization problems, a local optimum is easily converged, rather than for the expected global optimum. The enhanced diversity agent in optimal algorithms is one of the solutions to this issue. This paper proposes a novel optimization algorithm, namely BPO, based on the communication of the bees in artificial bee colony optimization (ABC), with the pollen in flower pollination algorithm (FPA) to solve the multimodal optimization problems. A new communication strategy for Bees and Pollens is presented to explore and exploit the diversity of the algorithm. Six multimodal benchmark functions are used to verify the convergent behavior, the accuracy, and the speed of the proposed algorithm. Experimental results show that the proposed scheme increases the accuracy more than the original algorithms.
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Qu, B.Y., Suganthan, P.N., Das, S.: A distance-based locally informed particle swarm model for multimodal optimization. IEEE Trans. Evol. Comput. 17(3), 387–402 (2013)
Wolfe, M., Banerjee, U.: Data dependence and its application to parallel processing. Int. J. Parallel Program. 16(2), 137–178 (1987)
Dao, T.-K., Pan, T.-S., Nguyen, T.-T., Chu, S.-C.: A compact articial bee colony optimization for topology control scheme in wireless sensor networks. J. Inf. Hiding Multimedia Sign. Proces. 6(2), 297–310 (2015)
Pan, T.-S., Dao, T.-K., Nguyen, T.-T., Chu, S.-C.: Optimal base station locations in heterogeneous wireless sensor network based on hybrid particle swarm optimization with bat algorithm. J. Comput. 25(4), 14–25 (2015)
Chu, S.C., Roddick, J.F., Pan, J.-S.: A parallel particle swarm optimization algorithm with communication strategies. J. Inf. Sci. Eng. 21(4), 1–9 (2005)
Whitley, D., Rana, S., Heckendorn, R.B.: The island model genetic algorithm: on separability, population size and convergence. J. Comput. Inf. Technol. 7(1305), 33–48 (1998)
Tsai, C.-F., Dao, T.-K., Yang, W.-J., Nguyen, T.-T., Pan, T.-S.: Parallelized bat algorithm with a communication strategy. In: Ali, M., Pan, J.-S., Chen, S.-M., Horng, M.-F. (eds.) IEA/AIE 2014, Part I. LNCS, vol. 8481, pp. 87–95. Springer, Heidelberg (2014)
Yang, X.-S.: Flower pollination algorithm for global optimization. In: Durand-Lose, J., Jonoska, N. (eds.) UCNC 2012. LNCS, vol. 7445, pp. 240–249. Springer, Heidelberg (2012)
Karaboga, D.: An idea based on honey bee swarm for numerical optimization. Technical report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, vol. T2005 (2005)
Karaboga, D., Gorkemli, B., Ozturk, C., Karaboga, N.: A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artif. Intell. Rev. 42(1), 21–57 (2014)
Wang, R., Zhou, Y.: Flower pollination algorithm with dimension by dimension improvement. Math. Probl. Eng. 2014, 9 (2014)
TSai, P.-W., Pan, J.-S., Liao, B.-Y., Chu, S.-C.: Enhanced artificial bee colony optimization. Int. J. Innovative Comput. Inf. Control 5(12), 5081–5092 (2009)
Wang, H., Sun, H., Li, C.H., Shahryar, R., Pan, J.-S.: Diversity enhanced particle swarm optimization with neighborhood search. Inf. Sci. 223, 119–135 (2013). 20 Feb 2013
Yao, X., Liu, Y., Lin, G.: Evolutionary programming made faster. IEEE Trans. Evol. Comput. 3(2), 82–102 (1999)
Suganthan, P.N., Hansen, N., Liang, J.J., Deb, K., Chen, Y.-P., Auger, A., Tiwari, S.: Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization. KanGAL report, vol. 2005 (2005)
Whitley, D.: A genetic algorithm tutorial. Stat. Comput. 4(2), 65–85 (1994)
Karaboga, D., Basturk, B.: On the performance of artificial bee colony (ABC) algorithm. Appl. Soft Comput. 8(1), 687–697 (2008)
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Pan, TS., Dao, TK., Nguyen, TT., Chu, SC., Pan, JS. (2016). Bees and Pollens with Communication Strategy for Optimization. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9622. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49390-8_63
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DOI: https://doi.org/10.1007/978-3-662-49390-8_63
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