Multi-objective evolutionary algorithms (MOEAs) have shown promising performance in
solving various optimization problems, but their performance may deteriorate drastically …

Credit card fraud is becoming a serious and growing problem as a result of the emergence
of innovative technologies and communication methods, such as contactless payment. In …

Multi-modal multi-objective optimization problem (MMOPs) has attracted more and more
attention in evolutionary computing recently. It is not easy to solve these problems using the …

In order to effectively solve multi-objective optimization problems (MOPs) and fully balance
uniformity and convergence, a multi-strategy competitive-cooperative co-evolutionary …

Evolutionary feature selection (FS) methods face the challenge of “curse of dimensionality”
when dealing with high-dimensional data. Focusing on this challenge, this article studies a …

Multimodal multiobjective problems (MMOPs) commonly arise in real-world situations where
distant solutions in decision space share a very similar objective value. Traditional …

Recently, the Slime mould algorithm (SMA) was proposed to solve the single-objective
optimization problems. It is considered as a strong algorithm for its efficient global search …

There exist many multiobjective optimization problems (MOPs) containing a large number of
decision variables in real-world applications, which are known as large-scale MOPs. Due to …

Finding a feasible solution set for optimization problems in conflict with objective functions
poses significant challenges. Moreover, in such problems, the level of complexity may …

In multiobjective optimization, the relationship between decision space and objective space
is generally assumed to be a one-to-one mapping, but it is not always the case. In some …