Resumo

GUERRERO ENAMORADO, Alain et al. Evaluation of Projects by using Genetic Rules Based Systems. Rev cuba cienc informat [online]. 2017, vol.11, n.4, pp. 39-56. ISSN 2227-1899.

In the present work is assessed the behavior of the evolutionary algorithm MCGEP in different versions of a project management database which contains information for projects evaluation. The main idea of this work is to confirm the possibility of applying an evolutionary algorithm that uses genetic expression programming in front of seven other widely used algorithms in the state of the art. The algorithms used in the assess are able to generate interpretable classification models, using evolutionary techniques to obtain them. The experiments were carried out in five versions created from the database with information of the projects evaluation. The MCGEP algorithm achieves the first among the algorithms compared for the predictive accuracy metric; also, it significantly improves the majority of these algorithms for this metric. On the other hand, the complexity of the generated models was acceptable to achieve these results, so MCGEP and GASSIST algorithms excel as the most balanced if both metrics are taken into account at the same time. As value added, we take advantage of the implicit process of feature selection capability that have these kinds of techniques. With this, we draw some conclusions about which are the measurement indicators that most influence the evaluation of a project and which indicators can detect in time which project will not achieve a good evaluation when finalized.

Palavras-chave : Genetic Algorithms; Gene Expression Programming; Algorithm MCGEP; Project Evaluation; Rules´ learning.

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