Abstract
Bat Algorithm (BA) is one of the fundamental algorithms for solving optimization problems. However, the BA still exists weaknesses in terms of exploitation and exploration. In this paper, an enhancing capability of exploration and exploitation for BA by hybridizing BA with Ant Lion Optimizer (ALO) is proposed for the global optimization problems. In the experimental section, several benchmark functions are used to test the performance of the proposed approach. Compared results with other algorithms literature show that the proposed method provides a new competitive algorithm.
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Nguyen, T.-T., Pan, J.-S., Dao, T.-K.: A novel improved bat algorithm based on hybrid parallel and compact for balancing an energy consumption problem. Information 10, 194 (2019)
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Dao, TK. et al. (2020). An Improved Bat Algorithm Based on Hybrid with Ant Lion Optimizer. In: Pan, JS., Lin, JW., Liang, Y., Chu, SC. (eds) Genetic and Evolutionary Computing. ICGEC 2019. Advances in Intelligent Systems and Computing, vol 1107. Springer, Singapore. https://doi.org/10.1007/978-981-15-3308-2_6
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DOI: https://doi.org/10.1007/978-981-15-3308-2_6
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