Swarm Intelligence Algorithms Inspired by Nature: A Review

Journal: المجلة العراقية للعلوم الاحصائية • • College of Computer Science and Mathematics, University of Mosul • ISSN: 1680-855X

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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How to Cite this Article

Safa R. Mahmood, Shahbaa I. Khaleel (2026). "Swarm Intelligence Algorithms Inspired by Nature: A Review". المجلة العراقية للعلوم الاحصائية. https://doi.org/10.33899/iqjoss.v23i1.62135