Journal Article

25 Years of Particle Swarm Optimization: Flourishing Voyage of Two Decades

Dhiman, Gaurav, Vimal, S., Naik, Bighnaraj, Swapnarekha, H., Nayak, Janmenjoy

2023

Overview

From the past few decades many nature inspired algorithms have been developed and gaining more popularity because of their effectiveness in solving problems of distinct application domains. Undoubtedly, Particle swarm optimization (PSO) algorithm is the most successful optimization algorithm among the available nature inspired algorithms such as simulated annealing, genetic algorithm, differential evolution, firefly, cuckoo etc., because of its high efficiency and capability to adjust in different dynamic environments. This year marks its 25th anniversary of PSO, one of the base inspirations for many modern-day metaheuristics development. Because of its simple structure and few number of algorithmic parameters, PSO from its origin has acquired widespread popularity amongst researchers, technocrats and practitioners and has been proven to provide better performance in various functional areas such as networking, robotics, image segmentation, power generation and controlling, fuzzy systems and so on. PSO is a population based global heuristic optimization approach motivated by the social behavior of animals chasing for food such as flock of birds, schools of fish. PSO attempts to stabilize exploration and exploitation by combining local search capabilities with global search capabilities. In this article, an in-depth analysis of PSO with its developments from 1995 to 2020 has been presented. Mainly, the improved variants of PSO along with solvable application areas are discussed in detail to provide a scope for the further development. At the end of the paper, the growth of the PSO in various application areas has been presented with factual representation. The main motive of this survey is to inspire the researchers, practitioners and technocrats to develop improved and innovative solutions for solving complex problems in various domains using PSO.

• Publisher: Springer Netherlands,Springer Nature B.V
• Subject: Bees / Chemistry / Design / Engineering / Evolutionary algorithms / Evolutionary computation / Food / Fuzzy systems / Genetic algorithms / Heuristic methods / Image segmentation / Literature reviews / Mathematical and Computational Engineering / Optimization algorithms / Optimization techniques / Particle swarm optimization / Problem solving / Review Article / Robotics / Schools (fish) / Simulated annealing / Taxonomy