GA/SA-based hybrid techniques for the scheduling of generator maintenance in power systems

Tools

Dahal, K.P. and Burt, G.M. and Mcdonald, J.R. and Galloway, S.J.; (2002) GA/SA-based hybrid techniques for the scheduling of generator maintenance in power systems. In: Proceedings of the 2000 Congress on Evolutionary Computation. IEEE, 567 - 574. ISBN 0-7803-6375-2 (https://doi.org/10.1109/CEC.2000.870347)

Full text not available in this repository.Request a copy

Abstract

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 problems

ORCID iDs

Dahal, K.P., Burt, G.M. ORCID logoORCID: https://orcid.org/0000-0002-0315-5919, Mcdonald, J.R. ORCID logoORCID: https://orcid.org/0000-0002-7078-845X and Galloway, S.J. ORCID logoORCID: https://orcid.org/0000-0003-1978-993X;
CORE (COnnecting REpositories)