Abstract— Evolutionary multi-objective optimization algorithms are commonly used to obtain a set of non-dominated solutions for over a decade. Recently, a lot of emphasis have be...
Karthik Sindhya, Ankur Sinha, Kalyanmoy Deb, Kaisa...
We present a statistical model of empirical optimization that admits the creation of algorithms with explicit and intuitively defined desiderata. Because No Free Lunch theorems di...
— Recently it has been proved that the (1+1)-EA produces poor worst-case approximations for the vertex cover problem. In this paper the result is extended to the (1+λ)-EA by pro...
Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which ...
In the paper, a new evolutionary algorithm (EA) for mixed tree learning is proposed. In non-terminal nodes of a mixed decision tree different types of tests can be placed, ranging ...