This paper presents a state-of-the-art review on multi-objective metaheuristics for multi-
objective discrete optimization problems (MODOPs). The relevant literature source and their …

Following decades of sustained improvement, metaheuristics are one of the great success
stories of optimization research. However, in order for research in metaheuristics to avoid …

Heuristics are widely used for dealing with complex search and optimization problems.
However, manual design of heuristics can be often very labour extensive and requires rich …

Optimization can be found in many real-life applications. Designing an effective algorithm for
a specific optimization problem typically requires a tedious amount of effort from human …

Feature selection (FS) is considered to be a hard optimization problem in data mining and
some artificial intelligence fields. It is a process where rather than studying all of the features …

Companies are constantly changing in their organization and the way they treat information.
In this sense, relevant data analysis processes arise for decision makers. Similarly, to …

Algorithm configuration (AC) is concerned with the automated search of the most suitable
parameter configuration of a parametrized algorithm. There is currently a wide variety of AC …

As complexity and capabilities of Artificial Intelligence technologies increase, so does its
potential for misuse. Deepfake videos are an example. They are created with generative …

Literature is prolific with metaheuristics for solving continuous optimisation problems. But, in
practice, it is difficult to choose one appropriately for several reasons. First and …

The particle swarm optimization (PSO) algorithm has been the object of many studies and
modifications for more than 25 years. Ranging from small refinements to the incorporation of …