Title: Rock Hyrax intelligent optimisation algorithm: an exploration for Web 3.0 domain selection

Authors: B. Suresh Kumar; Deepshikha Bhargava; Arpan Kumar Kar; Chinwe Peace Igiri

Addresses: Amity University, Jaipur, Rajasthan, India ' University of Petroleum and Energy Studies, Dehradun, India ' DMS, Indian Institute of Technology, Delhi, India ' Amity University, Jaipur, Rajasthan, India

Abstract: Currently, the immense growth of internet usage has become a bottleneck situation for web developers to meet the customer requirements. To analyse this changing scenario, the developers need to meet these requirements through the introduction of various optimisation techniques. Various enumerable optimisation techniques are available in the market to explore the Web 3.0 domain. In this research, the author proposed a new metaheuristic approach that aimed at providing an appropriate solution to the analysis and optimisation issues. The main aim to design this algorithm in spite of existing algorithms is for wider search space and less time for optimisation as based on the foraging time by Rock Hyraxes. Here, the swarm intelligence metaheuristic approach is proposed based on the biological behaviour of Rock Hyrax available in East Africa. This novel Rock Hyrax intelligent optimisation (RHIO) algorithm is designed to optimise the results in the Web 3.0 domain.

Keywords: metaheuristics; Web 3.0; optimisation; swarm intelligence; Rock Hyrax intelligent optimisation; RHIO.

DOI: 10.1504/IJAIP.2021.119017

International Journal of Advanced Intelligence Paradigms, 2021 Vol.20 No.3/4, pp.243 - 263

Received: 12 Oct 2017
Accepted: 24 Nov 2017
Published online: 18 Nov 2021 *

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