As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …

In the last few years, the formulation of real-world optimization problems and their efficient
solution via metaheuristic algorithms has been a catalyst for a myriad of research studies. In …

A recent set of overused population-based methods have been published in recent years.
Despite their popularity, most of them have uncertain, immature performance, partially done …

Metaheuristics are popularly used in various fields, and they have attracted much attention
in the scientific and industrial communities. In recent years, the number of new metaheuristic …

The leading approaches in Machine Learning are notoriously data-hungry. Unfortunately,
many application domains do not have access to big data because acquiring data involves a …

A bilevel programming model represents the relationship in a specific decision process that
involves decisions within a hierarchical structure of two levels. The upper-level problem is …

Artificial intelligence and all its supporting tools, eg machine and deep learning in
computational intelligence-based systems, are rebuilding our society (economy, education …

Bio-inspired optimization (including Evolutionary Computation and Swarm Intelligence) is a
growing research topic with many competitive bio-inspired algorithms being proposed every …

Cluster analysis is an essential tool in data mining. Several clustering algorithms have been
proposed and implemented, most of which are able to find good quality clustering results …

Defining the optimal parameters of the photovoltaic system (PV) models according to the
actual real voltage and current data is a crucial process during designing, emulating …