Using the Cuckoo Search for Generating New Particles in Particle Swarm Optimization Algorithm
- 1 Sulaimani Polytechnic University, Iraq
- 2 Qaiwan International University (QIU) Raparin, Iraq
Copyright: © 2020 Fariaa Abdalmajeed Hameed, Harith Raad Hasan, Ahmed Abdullah Ahmed and Gulala Ali Hama Amin. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
This study is focused on as Cuckoo Search (CS), one of the current meta-heuristic optimization algorithm. The CS algorithm is useful in generating and searching for the most optimum particles of important meta-heuristic optimization algorithm, known as the Particle Swarm Optimization (PSO), to enhance its performance. This optimization is confirmed through a benchmark online optimization and actual problems. The PSO algorithm performance is also compared with differing algorithms representative of the area. The CS optimal solutions outperform alternative current solutions as CS has distinct search features. The study findings have implications for future studies and practice.
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- Cuckoo Search (CS)
- Particle Swarm Optimization