Comprehensive Study of Population Based Algorithms DOI Open Access
Yam Krishna Poudel,

Jeewan Phuyal,

Rajiv Kumar

et al.

American Journal of Computer Science and Technology, Journal Year: 2024, Volume and Issue: 7(4), P. 195 - 217

Published: Dec. 23, 2024

The exponential growth of industrial enterprise has highly increased the demand for effective and efficient optimization solutions. Which is resulting to broad use meta heuristic algorithms. This study explores eminent bio-inspired population based techniques, including Particle Swarm Optimization (PSO), Spider Monkey (SMO), Grey Wolf (GWO), Cuckoo Search (CSO), Grasshopper Algorithm (GOA), Ant Colony (ACO). These methods which are inspired by natural biological phenomena, offer revolutionary problems solving abilities with rapid convergence rates high fitness scores. investigation examines each algorithm's unique features, properties, operational paradigms, conducting comparative analyses against conventional methods, such as search history, functions express their superiority. also assesses relevance, arithmetic andlogical efficiency, applications, innovation, robustness, andlimitations. findings show transformative potential these algorithms offering valuable wisdom future research enhance broaden upon methodologies. finding assists a guiding researchers enable inventive solutions in advancing field optimization.

Language: Английский

Enhancing Heart Disease Diagnosis with Meta-Heuristic Algorithms: A Combined HHO and PSO Approach DOI
Farzana Begum,

J. Arul Valan

Deleted Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 21, 2025

Language: Английский

Citations

0

Comprehensive Study of Population Based Algorithms DOI Open Access
Yam Krishna Poudel,

Jeewan Phuyal,

Rajiv Kumar

et al.

American Journal of Computer Science and Technology, Journal Year: 2024, Volume and Issue: 7(4), P. 195 - 217

Published: Dec. 23, 2024

The exponential growth of industrial enterprise has highly increased the demand for effective and efficient optimization solutions. Which is resulting to broad use meta heuristic algorithms. This study explores eminent bio-inspired population based techniques, including Particle Swarm Optimization (PSO), Spider Monkey (SMO), Grey Wolf (GWO), Cuckoo Search (CSO), Grasshopper Algorithm (GOA), Ant Colony (ACO). These methods which are inspired by natural biological phenomena, offer revolutionary problems solving abilities with rapid convergence rates high fitness scores. investigation examines each algorithm's unique features, properties, operational paradigms, conducting comparative analyses against conventional methods, such as search history, functions express their superiority. also assesses relevance, arithmetic andlogical efficiency, applications, innovation, robustness, andlimitations. findings show transformative potential these algorithms offering valuable wisdom future research enhance broaden upon methodologies. finding assists a guiding researchers enable inventive solutions in advancing field optimization.

Language: Английский

Citations

1