Self-adjusting population sizes for non-elitist evolutionary algorithms: why success rates matter.
Mario Alejandro Hevia FajardoDirk SudholtPublished in: GECCO (2021)
Keyphrases
- evolutionary algorithm
- success rate
- fitness sharing
- mutation operator
- population diversity
- evolution process
- multi objective
- initial population
- evolutionary process
- optimization problems
- fitness landscape
- evolutionary computation
- differential evolution
- evolutionary strategy
- fitness function
- genetic algorithm
- multi objective optimization
- genetic programming
- simulated annealing
- mutation rate
- nsga ii
- genetic operators
- estimation of distribution algorithms
- crossover operator
- island model
- evolutionary search
- premature convergence
- candidate solutions
- evolution strategy
- evolvable hardware
- search algorithm
- population size
- optimization method
- search space
- differential evolution algorithm
- benchmark problems
- binary search trees
- particle swarm optimization pso
- parallel algorithm
- optimization algorithm
- particle swarm optimization
- multiobjective evolutionary algorithms
- population based incremental learning