Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(25), P. 37732 - 37745
Published: May 24, 2024
Language: Английский
Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(25), P. 37732 - 37745
Published: May 24, 2024
Language: Английский
Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 358, P. 120756 - 120756
Published: April 9, 2024
Language: Английский
Citations
28Construction and Building Materials, Journal Year: 2024, Volume and Issue: 417, P. 135331 - 135331
Published: Feb. 1, 2024
Language: Английский
Citations
22Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 124971 - 124971
Published: March 20, 2025
Language: Английский
Citations
1Renewable Energy, Journal Year: 2024, Volume and Issue: 237, P. 121769 - 121769
Published: Oct. 30, 2024
Language: Английский
Citations
4Earth Systems and Environment, Journal Year: 2025, Volume and Issue: unknown
Published: March 24, 2025
Language: Английский
Citations
0Automation in Construction, Journal Year: 2024, Volume and Issue: 166, P. 105655 - 105655
Published: July 31, 2024
Language: Английский
Citations
1American 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
1Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(25), P. 37732 - 37745
Published: May 24, 2024
Language: Английский
Citations
0