Genetic algorithms solution to generator maintenance scheduling with modified genetic operators
โ Scribed by Baskar, S.; Subbaraj, P.; Rao, M.V.C.; Tamilselvi, S.
- Book ID
- 114452407
- Publisher
- The Institution of Electrical Engineers
- Year
- 2003
- Tongue
- English
- Weight
- 293 KB
- Volume
- 150
- Category
- Article
- ISSN
- 1350-2360
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In this paper we consider the problem of generator maintenance scheduling (GMS) in power systems. A genetic algorithm with a fuzzy evaluation function is proposed in order to overcome some of the limitations of conventional modelling and solution methods. A test GMS problem is formulated with a rel
Genetic algorithms (GA) have been widely used to solve planning problems. However, they require one to determine the optimal values of many genetic parameters, such as population sizes, crossover probability, mutation probability, and so on. To make matters worse, the most suitable combination of pa