Abstract
The foraging behavior of real honey bees inspired D. Karaboga to develop an algorithm, namely Artificial Bee Colony (ABC) Algorithm. The ABC performs well in comparison to other swarm-based algorithms but has few drawbacks also. Similar to other stochastic techniques, the step size during the position update play a very imperative part in the potential of ABC. The ABC is very good in the exploration of search space but not fine in exploitation. So, as to improve balancing between diversification and intensification process of ABC algorithm, a novel variation of ABC proposed termed as Arrhenius ABC (aABC) algorithm. The suggested algorithm tested over eight unconstrained global optimization functions and two constrained problems. The results prove that aABC algorithm performs better for considered low dimensional problems in comparison to basic ABC and its current variants.
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Kumar, S., Nayyar, A., Kumari, R. (2019). Arrhenius Artificial Bee Colony Algorithm. In: Bhattacharyya, S., Hassanien, A., Gupta, D., Khanna, A., Pan, I. (eds) International Conference on Innovative Computing and Communications. Lecture Notes in Networks and Systems, vol 56. Springer, Singapore. https://doi.org/10.1007/978-981-13-2354-6_21
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DOI: https://doi.org/10.1007/978-981-13-2354-6_21
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