Swarm Intelligence: Nature-Inspired Problem Solving

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2025 | Volume : 12 | 03 | Page :
    By

    V. Basil Hans,

  1. Research Professor, Department of Management & Commerce, Srinivas University, Mangalore, Karnataka, India

Abstract

Swarm Intelligence (SI) is a computational paradigm inspired by the collective behavior of natural systems, such as flocks of birds, schools of fish, and colonies of ants. It involves decentralized, self- organized systems where simple agents follow simple rules, yet their interactions lead to complex global behaviors. SI has gained significant attention in recent years due to its potential applications in solving optimization problems, routing, scheduling, and artificial intelligence tasks. Techniques like Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Artificial Bee Colony (ABC) have been successfully applied across various domains, including robotics, telecommunications, transportation, and bioinformatics. This article provides an overview of the principles and algorithms underlying Swarm Intelligence, highlighting its strengths in solving real-world problems and its ability to adapt to dynamic environments. Moreover, it explores current advancements and challenges in the field, including scalability, robustness, and convergence issues. By drawing parallels with nature’s efficiency, Swarm Intelligence presents an innovative and adaptive approach to problem-solving, with promising implications for the future of autonomous systems and intelligent decision-making.

Keywords: Autonomous systems, intelligent decision-making, behavioral controls, generation of signals

How to cite this article:
V. Basil Hans. Swarm Intelligence: Nature-Inspired Problem Solving. Journal of Software Engineering Tools & Technology Trends. 2025; 12(03):-.
How to cite this URL:
V. Basil Hans. Swarm Intelligence: Nature-Inspired Problem Solving. Journal of Software Engineering Tools & Technology Trends. 2025; 12(03):-. Available from: https://journals.stmjournals.com/josettt/article=2025/view=234900


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Ahead of Print Subscription Review Article
Volume 12
03
Received 23/03/2025
Accepted 22/08/2025
Published 27/12/2025
Publication Time 279 Days
58

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