The epiGenetic Algorithm (epiGA), consists of a set of strategies, based on evolutionary computation, inspired in nature, especially in epigenetics, with the aim of solving complex combinatorial problems. Java version https://gitlab.com/dhstolfi/epiGA Python version https://gitlab.com/dhstolfi/epiGA.py
Python library for artificial neural network (NN) optimization. https://github.com/acamero/dlopt
This is a framework in C++ to solve the p-median problem. https://github.com/cintrano/p-median
Java project to solve the bi-objective shortest path problem taking into account the uncertainty in the parameters.
This is an application for the collection of geolocalized data during a road trip using a mobile phone. https://github.com/cintrano/NEOTrack
JCell is a framework for working mainly with cellular genetic algorithms (cGAs), but also it has implemented steady-state GAs, generational GAs, and distributed GAs (only a sequential version with ssGAs in the islands). https://jcell.gforge.uni.lu/
Previous developments of the group