Abstract
Nowadays swarm intelligence (SI)-based techniques are emerging techniques in the field of optimization. Artificial bee colony (ABC) algorithm is a significant member in the area of SI-based strategies. This research propounds a local search (LS) strategy motivated by the generation of the Fibonacci sequence. Further, the propound LS strategy is integrated with ABC to enhance the exploitation behavior. The propound LS strategy is named as Fibonacci-inspired local search (FLS) strategy and the hybridized algorithm is termed as Fibonacci-inspired artificial bee colony (FABC) algorithm. In the propound LS strategy, the Fibonacci series equation is altered by incorporating the commitment and community-based learning elements of ABC algorithm. To analyze the potential of the propound strategy, it is analyzed over 31 benchmark optimization functions. The reported outcomes prove the validity of the propound approach. ...
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Sharma, N., Sharma, H., Sharma, A., Bansal, J.C. (2019). Fibonacci Series-Inspired Local Search in Artificial Bee Colony Algorithm. In: Yadav, N., Yadav, A., Bansal, J., Deep, K., Kim, J. (eds) Harmony Search and Nature Inspired Optimization Algorithms. Advances in Intelligent Systems and Computing, vol 741. Springer, Singapore. https://doi.org/10.1007/978-981-13-0761-4_96
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