A Proof that Using Crossover Can Guarantee Exponential Speed-Ups in Evolutionary Multi-Objective Optimisation.
Duc-Cuong DangAndre OprisBahare SalehiDirk SudholtPublished in: CoRR (2023)
Keyphrases
- multi objective optimisation
- genetic algorithm
- multi objective
- evolutionary algorithm
- nsga ii
- multi objective optimization
- evolutionary computation
- evolutionary optimization
- evolutionary process
- mutation rate
- crossover operator
- optimization algorithm
- evolutionary methods
- mutation operator
- genetic programming
- multiple objectives
- fitness function
- differential evolution
- crossover and mutation
- multiobjective optimization
- genetic search
- evolution process
- evolutionary search
- genetic algorithm ga
- particle swarm optimization
- complete axiomatization
- objective function
- theorem prover
- optimization problems
- simulated annealing
- pareto optimal
- linear logic
- island model
- genetic operators
- neural network
- fuzzy systems
- theorem proving
- search space