Adam Kunna Azrag, Mohammed and Tuty Asmawaty, Abdul Kadir and Noorlin, Mohd Ali (2020) A Comparison of Particle Swarm optimization and Global African Buffalo Optimization. In: IOP Conference Series: Materials Science and Engineering, 6th International Conference on Software Engineering and Computer Systems, ICSECS 2019 , 25 - 27 September 2019 , Vistana Hotel, Kuantan. pp. 1-12., 769 (012034). ISSN 1757-8981 (Print), 1757-899X (Online)
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Abstract
The performance of Particle Swarm Optimization (PSO) brings attention to the field of algorithms when deals with different optimization problems. Due to her simple implementation, small consumption, and very effective in finding a solution in many problems, (PSO) becomes well known to the field of algorithms. In addition, the late proposed algorithms mostly are compared to the well-known algorithm such as PSO. Thus, the Global African Buffalo Optimization (GABO) was proposed lately and yet not been compared to the old well-known algorithms in terms of accuracy and time consumption. However, in this paper, a comparison between Particle Swarm Optimization (PSO) and Global African Buffalo Optimization (GABO) algorithms was performed. Five different nonlinear equations with their upper and lower boundaries values were selected as the test optimization functions problem in addition to PSO was applied to real case study. The experimental results illustrated the differences in the performances of both algorithms toward the optimum solution. At the end of the experiments, the PSO algorithm quickly convergence towards the optimum solution using a few particles and iterations rather than GABO. However, the experimental result showed that PSO achieved good results in all the test cases within a short time. In many cases, PSO and GABO are promising optimization methods.
| Item Type: | Conference or Workshop Item (Lecture) |
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| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | PSO; GABO; Convergence; Sphere function; Rastrigrin function, Griewank function; Rosenbrock function; Shubert function |
| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76 Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Computing |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 13 Dec 2022 04:24 |
| Last Modified: | 13 Dec 2022 04:24 |
| URI: | http://umpir.ump.edu.my/id/eprint/28804 |
| Download Statistic: | View Download Statistics |
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