With the increase in available data from computer systems and their security threats, interest
in anomaly detection has increased as well in recent years. The need to diagnose faults and …

In this research, we investigate the application of machine learning techniques to
optimization problems and propose a novel integration between metaheuristics and …

Disease phenotypes are generally caused by the failure of gene modules which often have
similar biological roles. Through the study of biological networks, it is possible to identify the …

Community detection is one of the most challenging and interesting problems in many
research areas. Being able to detect highly linked communities in a network can lead to …

Bio-inspired algorithms are widely and successfully used in solving complex optimization
problems. However, a common challenge faced by these algorithms is getting stuck in local …

An immune metaheuristic has been developed for solving the Weighted Feedback Vertex
Set problem, known to be a NP-complete problem, which finds applicability in many real …

Community detection is a prominent research topic in Complex Network Analysis, and it
constitutes an important research field on all those areas where complex networks represent …

In this paper we present a hybrid immunological inspired algorithm (Hybrid-IA) for solving
the Minimum Weighted Feedback Vertex Set (MWFVS) problem. MWFVS is one of the most …

How long a B cell remains, evolves and matures inside a population plays a crucial role on
the capability for an immune algorithm to jump out from local optima, and find the global …

Hybrid algorithms are powerful search algorithms obtained by the combination of
metaheuristics with other optimization techniques, although the most common hybridization …