๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Genetic algorithms solution to generator maintenance scheduling with modified genetic operators

โœ 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

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Generator maintenance scheduling using a
โœ K.P. Dahal; C.J. Aldridge; J.R. McDonald ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 622 KB

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

Project scheduling using a genetic algor
โœ Tomoya Ikeuchi; Yoshitomo Ikkai; Dai Araki; Takenao Ohkawa; Norihisa Komoda ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 252 KB ๐Ÿ‘ 2 views

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