The decision-making process in oil fields includes a step of risk analysis associated with the
uncertainties present in the variables of the problem. Such uncertainties lead to hundreds …

In this work, we present a novel framework for automatic feature selection in brain-computer
interfaces (BCIs). The proposal, which manipulates features generated in the frequency …

A novel artificial immune system algorithm with social learning mechanisms (AIS‐SL) is
proposed in this paper. In AIS‐SL, candidate antibodies are marked with an elitist swarm …

This paper presents the OptBees, an optimization algorithm inspired by the processes of
collective decision-making by bee colonies. The algorithm was designed with the objective …

The aim of computer-aided musical orchestration (CAMO) is to find a combination of musical
instrument sounds that perceptually approximates a reference sound when played together …

Until recently, the main focus of researchers that develop algorithms for evolutionary multi-
objective optimization has been the creation of mechanisms capable of obtaining sets of …

Diversity maintenance is an important aspect in population-based metaheuristics for
optimization, as it tends to allow a better exploration of the search space, thus reducing the …

This paper presents OptBees, a new bee-inspired algorithm for solving continuous
optimization problems. Two key mechanisms for OptBees are introduced: 1) a local search …

Artificial immune system is one of the most recently introduced intelligence methods which
was inspired by biological immune system. Most immune system inspired algorithms are …

In practical engineering, multi-objective optimization often encounters situations where
multiple Pareto sets (PS) in the decision space correspond to the same Pareto front (PF) in …