GA/SA-based hybrid techniques for the scheduling of generator maintenance in power systems
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Proposes the application of a genetic algorithm (GA) and simulated annealing (SA) based hybrid approach for the scheduling of generator maintenance in power systems using an integer representation. The adapted approach uses the probabilistic acceptance criterion of simulated annealing within the genetic algorithm framework. A case study is formulated in this paper as an integer programming problem using a reliability-based objective function and typical problem constraints. The implementation and performance of the solution technique are discussed. The results in this paper demonstrate that the technique is more effective than approaches based solely on genetic algorithms or solely on simulated annealing. It therefore proves to be a valid approach for the solution of generator maintenance scheduling problemsCitation
Dahal, K.P., Burt, G.M., McDonald, J.R. and Galloway, S.J. (2000). GA/SA-based hybrid techniques for the scheduling of generator maintenance in power systems. Congress on Evolutionary Computation (CEC). La Jolla, CA, USA. 16-19 July 2000. Proceedings of the Congress on Evolutionary Computation. Vol. 1., pp. 567-574.Link to Version of Record
https://doi.org/10.1109/CEC.2000.870347Type
Conference paperae974a485f413a2113503eed53cd6c53
https://doi.org/10.1109/CEC.2000.870347