Swarm Intelligence Algorithms Inspired by Nature: A Review

Section: Review Articles
Issue
Vol. 23 No. 1 (2026): Volume 23 Issue 1
Published
May 31, 2026
Pages
149-162

Abstract

This work presents a comprehensive overview of nature-inspired optimization algorithms their components, classifications, and applications in various domains. The paper focuses on the importance of basic technique in swarm optimization algorithms such as:  Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Artificial Bee Colony Algorithm) ِABC), Salp Swarm Algorithm (SSA), Firefly Algorithm (FA), Grasshopper Optimization Algorithm (GOA), and other Swarm Intelligence Algorithms in solving complex problems. This study shows the classification of living organisms in order to classify and explore algorithms inspired by nature, and presents related works from (2020) to (2025), related to algorithms inspired by nature.

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Authors

Safa R. Mahmood
Shahbaa I. Khaleel

Identifiers

https://doi.org/10.33899/iqjoss.v23i1.62135
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How to Cite

Mahmood, S. R. ., & Khaleel, S. I. . (2026). Swarm Intelligence Algorithms Inspired by Nature: A Review. IRAQI JOURNAL OF STATISTICAL SCIENCES, 23(1), 149–162. https://doi.org/10.33899/iqjoss.v23i1.62135