Abstract
Biogeography-based optimization is meta-heuristic algorithm introduced by Dan Simon in early 2008. BBO’s capability of solving complex optimization problem is similar to that of PSO, ACO, ABC, DE, and GA. For ameliorating its strength to solving optimization problem relative to other heuristic techniques, it is required to modify the original BBO. Migration and mutation operator are two crucial features in BBO. Migration operator largely affects the performance of BBO. Therefore, for the improvement in BBO, migration is a potential step to modify. This paper studies the new migration operator in BBO which maintains both exploitation and exploration and provides a computational efficiency. The performance of proposed BBO is explored over 20 test problems and compared with basic BBO. Results show that proposed BBO algorithm outperforms over basic BBO algorithm.
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References
Dawei, D., Simon, D., Ergezer, M.: Biogeography-based optimization combined with evolutionary strategy and immigration refusal. In: IEEE International Conference on Systems, Man and Cybernetics, SMC 2009, pp. 997–1002, IEEE (2009)
Ma, H., Simon, D.: Blended biogeography-based optimization for constrained optimization. Eng. Appl. Artif. Intell. 24(3), 517–525 (2011)
Simon, D., Omran, M.G., Clerc, M.: Linearized biogeography-based optimization with re-initialization and local search. Inf. Sci. 267, 140–157 (2014)
Lohokare, M.R., Pattnaik, S.S., Panigrahi, B.K., Das, S.: Accelerated biogeography-based optimization with neighborhood search for optimization. Appl. Soft Comput. 13(5), 2318–2342 (2013)
Gong, W., Cai, Z., Ling, C.X., Li, H.: A real-coded biogeography-based optimization with mutation. Appl. Math. Comput. 216(9), 2749–2758 (2010)
Gong, W., Cai, Z., Ling, C.X.: De/bbo: a hybrid differential evolution with biogeography-based optimization for global numerical optimization. Soft Comput. 15(4), 645–665 (2012)
Ma, H.-P., Ruan, X.-Y., Pan, Z.-X.: Handling multiple objectives with biogeography-based optimization. Int. J. Autom. Comput. 9(1), 30–36 (2012)
Bansal, J.C., Sharma, H., Jadon, S.S., Clerc, M.: Spider monkey optimization algorithm for numerical optimization. Memetic Comput. 6(1), 31–47 (2014)
Simon, D.: Biogeography-based optimization. IEEE Trans. Evol. Comput. 12(6), 702–713 (2008)
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Farswan, P., Bansal, J.C. (2015). Migration in Biogeography-based Optimization. In: Das, K., Deep, K., Pant, M., Bansal, J., Nagar, A. (eds) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 336. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2220-0_31
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DOI: https://doi.org/10.1007/978-81-322-2220-0_31
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