Title: A conceptual comparison of metaheuristic algorithms and applications to engineering design problems
Authors: Kamalinder Kaur Kaleka; Avneet Kaur; Vijay Kumar
Addresses: Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab-147001, India ' Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab-147001, India ' Department of Computer Science and Engineering, National Institute of Technology, Hamirpur, Himachal Pradesh-177005, India
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.
Keywords: metaheuristic; spotted hyena optimiser; SHO; gravitational search algorithm; GSA; whale optimisation algorithm; WOA; moth flame optimisation; MFO.
International Journal of Intelligent Information and Database Systems, 2020 Vol.13 No.2/3/4, pp.278 - 306
Received: 16 Apr 2019
Accepted: 29 Oct 2019
Published online: 25 Aug 2020 *