• Akanksha Bansal Chopra Department of Computer Science, SPM College, University of Delhi, New Delhi, India
  • Monika Arora Department of Analytics/IT/Operations, Amity Business School, Amity University Haryana
  • Lavkush Gupta Department of Computer Science, SPM College, University of Delhi, New Delhi, India


Swarm Intelligence algorithms, meta heuristic, nature inspired


Swarm Intelligence algorithms are meta-heuristic and population-based stochastic optimization algorithms. These algorithms are influenced by an intelligent and  collective behaviour of insects or animals such as ants, fireflies, dragonflies, wolves, cuckoo, hawks etc. The behaviour of these insects and animals offers information and strategy to win the hunts in their own way. Their behaviour of hunting uses an optimised approach i.e. they win over their prey by using least number of hunting steps. The algorithms are developed on the basis of their behaviour to solve the real-world problems. This research paper presents a comparative study of various swarm intelligence optimization algorithms.


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How to Cite

Akanksha Bansal Chopra, Monika Arora, & Lavkush Gupta. (2023). A COMPARATIVE STUDY ON SWARM INTELLIGENCE ALGORITHMS. International Education and Research Journal (IERJ), 9(5). Retrieved from http://ierj.in/journal/index.php/ierj/article/view/2753