Hybrid-Fitness Function Evolutionary Algorithm Based on Simplex Crossover and PSO Mutation for Constrained Optimization Problems.
Yibo HuPublished in: Int. J. Pattern Recognit. Artif. Intell. (2009)
Keyphrases
- fitness function
- constrained optimization problems
- evolutionary algorithm
- crossover operator
- differential evolution
- genetic algorithm ga
- mutation operator
- constraint handling
- particle swarm optimization pso
- evolutionary computation
- genetic programming
- optimization problems
- multi objective
- particle swarm optimisation
- genetic operators
- genetic algorithm
- particle swarm
- crossover and mutation
- penalty function
- candidate solutions
- multi objective optimization
- mutation operation
- evolutionary process
- cauchy mutation
- selection strategy
- differential evolution algorithm
- simulated annealing
- function optimization
- evolutionary search
- initial population
- evolutionary strategy
- biogeography based optimization
- evolution strategy
- optimization method
- particle swarm optimization
- convergence speed
- fitness evaluation
- pso algorithm
- genetic algorithm is employed
- hybrid algorithm
- fitness values
- nsga ii
- mutation rate
- population diversity
- global optimization
- binary particle swarm optimization
- fitness landscape
- optimization algorithm
- test functions
- swarm intelligence