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.
CITATION STYLE
Vamsi Krishna, A. K., & Tyagi, T. (2021). Improved whale optimization algorithm for numerical optimization. In Advances in Intelligent Systems and Computing (Vol. 1086, pp. 59–71). Springer. https://doi.org/10.1007/978-981-15-1275-9_6
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