Sistema de inferencia borroso basado en redes adaptativas para la evaluación de proyectos

Anié Bermudez Peña, José Alejandro Lugo García, Pedro Yobanis Piñero Pérez


In this article, a set of key management indicators related to performance of execution, planning, costs, effectiveness, human resources, data quality, and logistics, are considered for the evaluation of a project. Several automated tools support project managers in this task. However, these tools are still insufficient to accurately assess projects in organizations with continuous improvement management styles and with presence of uncertainty in the primary data. An alternative solution is the introduction of soft computing techniques, allowing gains in robustness, efficiency, and adaptability in these tools. This paper presents an adaptivenetwork- based fuzzy inference system (ANFIS) to optimize projects evaluation made with the Xedro-GESPRO tool. The implementation of the system allowed the adjustment of fuzzy sets parameters in the inference rules for the assessment of projects, based on the automatic calculation of indicators. The contribution of this research lies in the application of ANFIS soft computing technique to optimize the evaluation of projects integrated with the management tool. The results contribute to the improvement of existing decision-making support tools into organizations towards project-oriented production. 


ANFIS, soft computing, evaluación de proyectos, sistema de inferencia borroso, toma de decisiones.

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