Among the many interesting meta-heuristic optimization algorithms, one can find those inspired by both the swarm and social behavior of human beings. The Brain Storm Optimization (BSO) is motivated by the brainstorming ...

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a ...

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be in-viable for a ...

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be in-viable for a ...

Given a positive and unitarily invariant Lagrangian L defined in the algebra of matrices, and a fixed time interval [0, t0 ] ⊂ ℝ, we study the action defined in the Lie group of n × n unitary matrices U(n) by, where α: [0, ...

Following the study of Andrade et al. (2009) on regular square lattices, here we investigate the problem of optimal path cracks (OPC) in Complex Networks. In this problem we associate to each site a determined energy. The ...

Feature selection stands for the process of finding the most relevant subset of features based on some criterion, which turns out to be an optimization task. In this context, several metaheuristic techniques have been ...