Behavior of EMO algorithms on many-objective optimization problems with correlated objectives.
Hisao IshibuchiNaoya AkedoHiroyuki OhyanagiYusuke NojimaPublished in: IEEE Congress on Evolutionary Computation (2011)
Keyphrases
- optimization problems
- benchmark problems
- np hard problems
- computational problems
- significant improvement
- learning algorithm
- hard problems
- difficult problems
- search methods
- benchmark datasets
- np complete
- computational cost
- multiple objectives
- practical problems
- evolutionary algorithm
- approximate solutions
- data structure
- computationally hard
- machine learning algorithms
- orders of magnitude
- high dimensionality
- computational complexity
- greedy algorithms
- data mining