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Generational and steady state genetic algorithms for generator maintenance scheduling problems
Dahal, Keshav P. McDonald, J.R.
Dahal, Keshav P.
McDonald, J.R.
Publication Date
1997
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© 1997 International Conference on Adaptive and Natural Computing Algorithms.
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Accepted for publication
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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
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).
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Type
Conference paper