Assessment of Genetic Algorithm selection, crossover and mutation techniques in reactive power optimization.
Muhammad Tami Al-HajriMohammad A. AbidoPublished in: IEEE Congress on Evolutionary Computation (2009)
Keyphrases
- crossover and mutation
- genetic algorithm
- reactive power optimization
- premature convergence
- genetic operators
- fitness function
- mutation operator
- multi objective optimization
- genetic algorithm ga
- power system
- evolutionary algorithm
- particle swarm
- differential evolution
- crossover and mutation operators
- genetic search
- hybrid algorithm
- multi objective
- simulated annealing
- initial population
- global search
- neural network
- pso algorithm
- optimization method
- evolutionary computation
- particle swarm optimization
- fuzzy logic
- artificial intelligence
- fitness landscape
- convergence speed
- swarm intelligence
- solution space
- crossover operator
- mutation probability
- search algorithm
- convergence rate
- tabu search
- dynamic programming
- artificial neural networks