Using Headless Chicken Crossover for Local Guide Selection When Solving Dynamic Multi-objective Optimization.
Mardé HelbigAndries P. EngelbrechtPublished in: NaBIC (2015)
Keyphrases
- multi objective optimization
- evolutionary algorithm
- crossover and mutation
- multi objective
- genetic algorithm
- differential evolution
- solving multi objective optimization problems
- bi objective
- evolutionary computation
- pareto optimal
- selection strategy
- multi objective optimization problems
- genetic programming
- nsga ii
- multiple objectives
- fitness function
- mutation operator
- optimization algorithm
- multi objective genetic algorithm
- crossover operator
- single objective optimization
- genetic operators
- optimization problems
- multi objective genetic algorithms
- combinatorial optimization
- particle swarm optimization
- genetic algorithm ga
- pareto dominance
- optimum design
- complex optimization problems
- pareto frontier
- neural network