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Research Article · Open access · Published 30 April 2020

Using the Cuckoo Search for Generating New Particles in Particle Swarm Optimization Algorithm

Fariaa Abdalmajeed Hameed1, Harith Raad Hasan1, Ahmed Abdullah Ahmed2 & Gulala Ali Hama Amin1

Journal of Computer Science, Volume 16, Issue 4, pp. 430–438 · doi.org/10.3844/jcssp.2020.430.438

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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.

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Hameed, F. A., Hasan, H. R., Ahmed, A. A. & Amin, G. A. H. (2020). Using the Cuckoo Search for Generating New Particles in Particle Swarm Optimization Algorithm. Journal of Computer Science, 16(4), 430–438. https://doi.org/10.3844/jcssp.2020.430.438

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Using the Cuckoo Search for Generating New Particles in Particle Swarm Optimization AlgorithmJournal of Computer Science · Volume 16, Issue 4 · pp. 430–438 · CC BY 3.0Download