The aim of this paper is to study surrogate-assisted algorithms for expensive multiobjective
combinatorial optimization problems. Targeting pseudo-boolean domains, we provide a fine …

The field of adversarial textual attack has significantly grown over the past few years, where
the commonly considered objective is to craft adversarial examples (AEs) that can …

Surrogate-assisted evolutionary algorithms for expensive optimization problems have
gained considerable attention in recent years. In many real-world optimization problems, we …

When it comes to solving optimization problems with evolutionary algorithms (EAs) in a
reliable and scalable manner, detecting and exploiting linkage information, that is …

In the context of pseudo-Boolean optimization, surrogate functions based on the Walsh-
Hadamard transform have been recently proposed with great success. It has been shown …

Model-Based Evolutionary Algorithms (MBEAs) can be highly scalable by virtue of linkage
(or variable interaction) learning. This requires, however, that the linkage model can capture …

Combinatorial optimization problems can involve computationaly expensive fitness function,
making their resolution challenging. Surrogate models are one of the effective techniques …

FS is essentially a combinatorial optimization problem that attempts to find the best subset of
2− 1 possible feature subsets from a given dataset with features [Wang et al., 2020]. When …

In the context of pseudo-Boolean optimization, surrogate functions based on the Walsh-
Hadamard transform have been recently proposed with great success. It has been shown …