Crossover can guarantee exponential speed-ups in evolutionary multi-objective optimisation.
Duc-Cuong DangAndre OprisDirk SudholtPublished in: Artif. Intell. (2024)
Keyphrases
- multi objective optimisation
- multi objective
- genetic algorithm
- evolutionary algorithm
- nsga ii
- evolutionary optimization
- evolutionary computation
- multi objective optimization
- evolutionary process
- mutation rate
- differential evolution
- mutation operator
- crossover operator
- multiobjective optimization
- genetic programming
- fitness function
- pareto optimal
- evolutionary methods
- optimization algorithm
- evolution process
- multiple objectives
- evolutionary search
- particle swarm optimization
- genetic algorithm ga
- genetic search
- optimization problems
- exponential size
- population size
- test problems
- linear complexity
- search problems
- selection strategy
- genetic operators
- fuzzy logic
- data sets
- computational complexity
- moving target defense