Using mixed mode programming to parallelize an indicator-based evolutionary algorithm for inferring multiobjective phylogenetic histories.
Sergio Santander-JiménezMiguel A. Vega-RodríguezPublished in: Soft Comput. (2017)
Keyphrases
- genetic operators
- evolutionary algorithm
- multi objective
- mixed mode
- code generation
- fitness function
- multi objective optimization
- evolutionary computation
- optimization problems
- optimization algorithm
- genetic programming
- genetic algorithm
- differential evolution
- mutation operator
- particle swarm optimization
- multiple objectives
- multiobjective optimization
- simulated annealing
- nsga ii
- application development
- pareto optimal
- multiobjective evolutionary algorithms
- parallel processing
- parallel algorithm
- service oriented
- genetic algorithm ga
- data driven
- multi objective evolutionary algorithms
- multi objective optimization problems
- database
- function optimization
- multiobjective evolutionary algorithm
- swarm intelligence
- web applications
- multi objective problems
- end users