Generational and steady state genetic algorithms for generator maintenance scheduling problems
| dc.contributor.author | Dahal, Keshav P. | * |
| dc.contributor.author | McDonald, J.R. | * |
| dc.date.accessioned | 2009-03-05T11:22:46Z | |
| dc.date.available | 2009-03-05T11:22:46Z | |
| dc.date.issued | 1997 | |
| dc.identifier.citation | Dahal, K. P. and McDonald, J. R. (1997) Generational and steady state genetic algorithms for generator maintenance scheduling problems. In: International Conference on Adaptive and Natural Computing Algorithms 1997, Norwich, England (ICANNGA '97). | en |
| dc.identifier.uri | http://hdl.handle.net/10454/2453 | |
| dc.description.abstract | The aim of generator maintenance scheduling (GMS) in an electric power system is to allocate a proper maintenance timetable for generators while maintaining a high system reliability, reducing total production cost, extending generator life time etc. In order to solve this complex problem a genetic algorithm technique is proposed here. The paper discusses the implementation of GAs to GMS problems with two approaches: generational and steady state. The results of applying these GAs to a test GMS problem based on a practical power system scenario are presented and analysed. The effect of different GA parameters is also studied | en |
| dc.language.iso | en | en |
| dc.rights | © 1997 International Conference on Adaptive and Natural Computing Algorithms. | en |
| dc.subject | Maintenance scheduling | en |
| dc.subject | Power generators | en |
| dc.subject | Electric power systems | en |
| dc.subject | Genetic algorithms | en |
| dc.subject | Reliability | en |
| dc.title | Generational and steady state genetic algorithms for generator maintenance scheduling problems | en |
| dc.status.refereed | Yes | en |
| dc.type | Conference paper | en |
| dc.type.version | Accepted Manuscript | en |
| refterms.dateFOA | 2018-07-18T13:33:18Z |
