A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems.
Jakob VesterstromRené ThomsenPublished in: IEEE Congress on Evolutionary Computation (2004)
Keyphrases
- differential evolution
- benchmark problems
- evolutionary algorithm
- optimization problems
- particle swarm optimization
- simulated annealing
- multi objective
- differential evolution algorithm
- convergence speed
- test problems
- test functions
- mutation operator
- evolutionary computation
- particle swarm
- constrained optimization problems
- metaheuristic
- particle swarm optimization pso
- premature convergence
- population diversity
- genetic algorithm
- multi objective optimization
- pso algorithm
- hybrid algorithm
- optimization method
- evolution strategy
- biogeography based optimization
- optimization algorithm
- genetic programming
- global optimization problems
- fitness function
- evolutionary programming
- optimisation problems
- job shop scheduling problem
- multi objective optimization problems
- solving global optimization problems
- particle swarm optimization algorithm
- numerical optimization problems
- global optimization
- parameter optimization
- swarm intelligence
- evolutionary methods
- solution quality
- optimization methods
- global search
- genetic algorithm ga
- vehicle routing problem
- tabu search
- evolutionary search
- evolutionary strategy
- initial population
- opposition based learning
- ant colony optimization
- inertia weight
- artificial bee colony
- nsga ii
- multiobjective optimization problems
- linear programming
- crossover operator