Abstract
In this paper, an Improved Whale Optimization Algorithm which is intended towards the better optimization of the solutions under the category of meta-heuristic algorithms is proposed. Falling under the genre of nature-inspired algorithms, the Improved Whale Optimization delivers better results with comparatively better convergence techniques used. A detailed study and comparative analysis have been made between the principal and the modified algorithms, and a variety of fitness functions has been used to confirm the efficiency of the improved algorithm over the older version. The merits with nature-inspired algorithms include distributed computing, reusable components, network processes, mutations and crossovers leading to better results, randomness and stochasticity.
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Vamsi Krishna, A.K., Tyagi, T. (2021). Improved Whale Optimization Algorithm for Numerical Optimization. In: Gao, XZ., Tiwari, S., Trivedi, M., Mishra, K. (eds) Advances in Computational Intelligence and Communication Technology. Advances in Intelligent Systems and Computing, vol 1086. Springer, Singapore. https://doi.org/10.1007/978-981-15-1275-9_6
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DOI: https://doi.org/10.1007/978-981-15-1275-9_6
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