A conceptual comparison of metaheuristic algorithms and applications to engineering design problems. (25th August 2020)

• Record Type: Journal Article
• Authors: Kaleka, Kamalinder Kaur; Kaur, Avneet; Kumar, Vijay
• Is Part Of: International journal of intelligent information and database systems. Volume 13:Number 2/4(2020)
• Page Start: 278
• Page End: 306
• Publication Date: 2020-08-25
• Subjects: metaheuristic -- spotted hyena optimiser -- SHO -- gravitational search algorithm -- GSA -- whale optimisation algorithm -- WOA -- moth flame optimisation -- MFO; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

This paper presents conceptual comparison among spotted hyena optimiser, grey wolf optimiser, particle swarm optimisation, ant colony optimisation, gravitational search algorithm, bat algorithm, moth flame optimisation, and whale optimisation algorithm. The behaviour of these algorithms is mathematical modelled to show the optimisation process. Twenty-three benchmark test functions are used to validate the performance of these algorithms. The exploration and exploitation of these algorithms are analysed using convergence curve. The experimental results depict that spotted hyena optimiser and grey wolf optimiser give optimal solutions as compared to the other algorithms. Furthermore, these algorithms are tested on five constrained engineering design problems. Experimental results reveal the applicability of these algorithms in real-life engineering design problems.