Add to ORKGNew Artificial Intelligence (AI) approaches such as simulated annealing, genetic algorithms, simulated evolution, neural networks, tabu search, fuzzy logic and their hybrid techniques have been applied in recent years to solving Generator Maintenance Scheduling (GMS) problems. This paper presents a review of these AI approaches for the GMS problem. The formulation of problems and the methodologies of solution are discussed and analysed. A case study is also included which presents the application of a genetic algorithm to a test system based on a practical power system scenario
The solution of generation scheduling (GS) problems involves the determination of the unit commitmen...
A new heuristic algorithm based on the Tabu search has been proposed for the maintenance schedule (M...
Abstract Generation maintenance scheduling (GMS) is an important and effective part of Generation ex...
YesProposes the application of a genetic algorithm (GA) and simulated annealing (SA) based hybrid ap...
The effective maintenance scheduling of power system generators is very important to a power utilit...
NoThe effective maintenance scheduling of power system generators is very important for the economic...
Abstract – The maintenance of generating units is implicitly related to power system reliability and...
Genetic algorithms become popular as a powerful optimisation tool suitable for a variety of problems...
Generator maintenance scheduling presents many engineering issues that provide power system personne...
This paper presents a modified discrete particle swarm optimization (PSO) based technique for genera...
This paper presents a genetic algorithm (GA) approach for solving the generators scheduling problem ...
The complexity of power systems is increasing as new generating units are added to power systems in...
The generation planning and investment problem in restructured industry is to determine what, when, ...
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Op...
10.1109/PMAPS.2010.55290042010 IEEE 11th International Conference on Probabilistic Methods Applied t...
The solution of generation scheduling (GS) problems involves the determination of the unit commitmen...
A new heuristic algorithm based on the Tabu search has been proposed for the maintenance schedule (M...
Abstract Generation maintenance scheduling (GMS) is an important and effective part of Generation ex...
YesProposes the application of a genetic algorithm (GA) and simulated annealing (SA) based hybrid ap...
The effective maintenance scheduling of power system generators is very important to a power utilit...
NoThe effective maintenance scheduling of power system generators is very important for the economic...
Abstract – The maintenance of generating units is implicitly related to power system reliability and...
Genetic algorithms become popular as a powerful optimisation tool suitable for a variety of problems...
Generator maintenance scheduling presents many engineering issues that provide power system personne...
This paper presents a modified discrete particle swarm optimization (PSO) based technique for genera...
This paper presents a genetic algorithm (GA) approach for solving the generators scheduling problem ...
The complexity of power systems is increasing as new generating units are added to power systems in...
The generation planning and investment problem in restructured industry is to determine what, when, ...
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Op...
10.1109/PMAPS.2010.55290042010 IEEE 11th International Conference on Probabilistic Methods Applied t...
The solution of generation scheduling (GS) problems involves the determination of the unit commitmen...
A new heuristic algorithm based on the Tabu search has been proposed for the maintenance schedule (M...
Abstract Generation maintenance scheduling (GMS) is an important and effective part of Generation ex...