Artificial intelligence techniques for optimizing the efficiency in public works contracting selection processes

• Autor: Solís-Villanueva, Reiner
• Formato: artículo
• Fecha de Publicación: 2018
• Institución: Universidad de Lima
• Repositorio: Revistas - Universidad de Lima
• Lenguaje: español
• OAI Identifier: oai:ojs.pkp.sfu.ca:article/2951
• Enlace del recurso: https://revistas.ulima.edu.pe/index.php/Interfases/article/view/2951
• Nivel de acceso: acceso abierto
• Materia: artificial neural networks; decision-making; risk; redes neuronales artificiales; toma de decisiones; riesgo

The present article proposes to design a model that provides a generic architecture which acts autonomously in public works contracting selection processes, in order to generate an automated decision criterion in the event of a tie. For the Simplified Tender selection process, in case of a tie, it is proposed to choose the bidder by means of an electronic lottery based on a controlled randomization system of encryption and transformation. For the Public Bidding selection process, in the event of a tie, the bidder is chosen by means of a predicted compliance index according to the behavior of the companies when executing similar infrastructure projects. To this end, a model that predicts the probability of success or failure of the bidder to execute a project before initiating it is generated, using artificial neural networks as an analysis tool. This paper reviews the common characteristics of artificial neural networks.