Most real-world problems involve some type of optimization problems that are often
constrained. Numerous researchers have investigated several techniques to deal with …

Grouping problems are combinatorial optimization problems, most of them NP-hard, related
to the partition of a set of items into different groups or clusters. Given their numerous real …

In this paper we present a novel grouping genetic algorithm for clustering problems. Though
there have been different approaches that have analyzed the performance of several …

This research paper aims to develop a hybrid neuro-evolutionary wrapper-based model for
daily global solar radiation estimation in the solar-rich Sunshine State of Queensland …

Grouping problems are a special type of combinatorial optimization problems that have
gained great relevance because of their numerous real-world applications. The solution …

This paper proposes a novel hybrid approach for feature selection in two different relevant
problems for marine energy applications: significant wave height (H m 0) and wave energy …

This paper provides a survey of the most important repair heuristics used in evolutionary
algorithms to solve constrained optimization problems. Popular techniques are reviewed …

In the last years, Bayesian optimization (BO) has emerged as a practical tool for high-quality
parameter selection in prediction systems. BO methods are useful for optimizing black-box …

The incorporation of collaborative work in the educational field grows day after day, as does
the research associated with this topic. One of the most recurring problems faced by …

As the perishable products market grows, the cold chain system is getting more attention. It
is desirable for perishable products to keep a good control throughout the whole logistics …