Abstract
A swarm is a group of a single species in which the members interact with one another and with theimmediate environment without a principle for control or the emergence of a global intriguing behavior. Swarm-basedmetaheuristics, including nature-inspired populace-based methods, have been developed to aid the creation of quick,robust, and low-cost solutions for complex problems. Swarm intelligence was proposed as a computational modelingof swarms and has been successfully applied to numerous optimization tasks since its introduction. A correlationwith the fundamental Particle Swarm Optimization (PSO) and PSO modifications demonstrates that hybrid swarmoptimization outperforms existing strategies. The downside of hybrid swarm optimization is that it frequently tendsto arrive at suboptimal solutions. As such, efforts are being made into combining HSO and other algorithms to arriveat better quality solutions.
Recommended Citation
Hasan, Raed A.; Najim, Suhe Shahab; and Ahmed, Munef Abdullah
(2021)
"Correlation with the fundamental PSO and PSO modifications tobe hybrid swarm optimization,"
Iraqi Journal for Computer Science and Mathematics: Vol. 2:
Iss.
2, Article 4.
DOI: https://doi.org/10.52866/ijcsm.2021.02.02.004
Available at:
https://ijcsm.researchcommons.org/ijcsm/vol2/iss2/4
