Most symbolic classifiers aim at building sets of rules with good coverage and precision. While this is suitable for most applications, they tend to neglect other desirable proper...
Rafael Giusti, Gustavo E. A. P. A. Batista, Ronald...
A hybrid Multi-Objective Evolutionary Algorithm is used to tackle the uncapacitated exam proximity problem. In this hybridization, local search operators are used instead of the tr...
Embedded systems have an ever-increasing need for optimizing compilers to produce high quality codes with a limited general purpose register set. Either memory or registers are use...
Abstract. Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Paret...
1 In most real world optimization problems several optimization goals have to be considered in parallel. For this reason, there has been a growing interest in Multi-Objective Optim...