A comparative approach of single-objective optimization algorithms for energy control of flexible manufacturing system
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| Titel: | A comparative approach of single-objective optimization algorithms for energy control of flexible manufacturing system |
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| Autoren: | Marius-Adrian PĂUN, Eugenia MINCĂ, Sergiu Stelian ILIESCU, Nicoleta ARGHIRA, Florin DRAGOMIR |
| Quelle: | Revista Română de Informatică și Automatică, Vol 35, Iss 2, Pp 43-58 (2025) |
| Verlagsinformationen: | ICI Bucharest, 2025. |
| Publikationsjahr: | 2025 |
| Schlagwörter: | T59.5, gray wolf optimization (gwo), Automation, genetic algorithms (ga), ant colony optimization (aco), particle swarm optimization (pso), flexible manufacturing system (fms), Information technology, T58.5-58.64 |
| Beschreibung: | This study presents a comparative analysis of the effectiveness of single-objective algorithms in optimizing automated process control. The research is conducted on a flexible manufacturing system (FMS) comprising seven production stations, each equipped with an energy consumption monitoring system. The objective is to examine how the optimization algorithms can contribute to enhancing the operational efficiency of the production systems. The study evaluates several single-objective algorithms ‒ Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), Ant Colony Optimization (ACO) to assess their potential for energy optimization in flexible manufacturing processes on FMS. Each algorithm's strengths and limitations are discussed with respect to their effectiveness in minimizing energy consumption and enhancing system performance. A comparative evaluation of the results obtained through the implementation and testing of each algorithm highlighted the superiority of the GWO algorithm. |
| Publikationsart: | Article |
| ISSN: | 1841-4303 1220-1758 |
| DOI: | 10.33436/v35i2y202504 |
| Zugangs-URL: | https://doaj.org/article/964688ce7c1a409ba5ac194a60802b85 |
| Dokumentencode: | edsair.doi.dedup.....168e7c2659cac8a3c99706e42e52e46d |
| Datenbank: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstract: | This study presents a comparative analysis of the effectiveness of single-objective algorithms in optimizing automated process control. The research is conducted on a flexible manufacturing system (FMS) comprising seven production stations, each equipped with an energy consumption monitoring system. The objective is to examine how the optimization algorithms can contribute to enhancing the operational efficiency of the production systems. The study evaluates several single-objective algorithms ‒ Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), Ant Colony Optimization (ACO) to assess their potential for energy optimization in flexible manufacturing processes on FMS. Each algorithm's strengths and limitations are discussed with respect to their effectiveness in minimizing energy consumption and enhancing system performance. A comparative evaluation of the results obtained through the implementation and testing of each algorithm highlighted the superiority of the GWO algorithm. |
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| ISSN: | 18414303 12201758 |
| DOI: | 10.33436/v35i2y202504 |