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    Generational and steady state genetic algorithms for generator maintenance scheduling problems

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    1998-icannga97-gms.pdf (29.40Kb)
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    Publication date
    1997
    Author
    Dahal, Keshav P.
    McDonald, J.R.
    Keyword
    Maintenance scheduling
    Power generators
    Electric power systems
    Genetic algorithms
    Reliability
    Rights
    © 1997 International Conference on Adaptive and Natural Computing Algorithms.
    Peer-Reviewed
    Yes
    
    Metadata
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    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
    URI
    http://hdl.handle.net/10454/2453
    Version
    Accepted Manuscript
    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).
    Type
    Conference paper
    Collections
    Engineering and Informatics Publications

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