For years, extensive research has been in the binarization of continuous metaheuristics for
solving binary-domain combinatorial problems. This paper is a continuation of a previous …

Feature selection is becoming a relevant problem within the field of machine learning. The
feature selection problem focuses on the selection of the small, necessary, and sufficient …

In this work, an approach is proposed to solve binary combinatorial problems using
continuous metaheuristics. It focuses on the importance of binarization in the optimization …

Currently, industry is undergoing an exponential increase in binary-based combinatorial
problems. In this regard, metaheuristics have been a common trend in the field in order to …

Chaotic maps are sources of randomness formed by a set of rules and chaotic variables.
They have been incorporated into metaheuristics because they improve the balance of …

When we face real problems using computational resources, we understand that it is
common to find combinatorial problems in binary domains. Moreover, we have to take into …

In recent years, continuous metaheuristics have been a trend in solving binary-based
combinatorial problems due to their good results. However, to use this type of …

Optimization techniques, specially metaheuristics, are constantly refined in order to
decrease execution times, increase the quality of solutions, and address larger target cases …

The structural design of civil works is closely tied to empirical knowledge and the design
professional's experience. Based on this, adequate designs are generated in terms of …

In this article, we propose the integration of a novel reinforcement learning technique into
our generic and unified framework. This framework enables any continuous metaheuristic to …