@article {10.3844/jcssp.2020.430.438,
article_type = {journal},
title = {Using the Cuckoo Search for Generating New Particles in Particle Swarm Optimization Algorithm},
author = {Hameed, Fariaa Abdalmajeed and Hasan, Harith Raad and Ahmed, Ahmed Abdullah and Amin, Gulala Ali Hama},
volume = {16},
number = {4},
year = {2020},
month = {Apr},
pages = {430-438},
doi = {10.3844/jcssp.2020.430.438},
url = {https://thescipub.com/abstract/jcssp.2020.430.438},
abstract = {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.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}