Constructivo GRASP para la optimización de una planta de producción en la industria automotriz

Abstract

Este artículo aborda un problema de planificación de la producción en la fabri- cación de asientos para automóviles. Ante la complejidad de múltiples líneas de producción y la diversidad de los productos a producir, se propone un algorit- mo heurístico basado en la metaheurística GRASP. El objetivo del algoritmo es encontrar soluciones factibles al problema y minimizar los costosos cambios de configuración, manteniendo los niveles de inventario dentro de los rangos deseados. La efectividad del algoritmo se valida comparándolo con un modelo exacto, demos- trando su capacidad para generar soluciones factibles y eficaces para la mayoría de los casos reales estudiados. Los resultados confirman la utilidad del enfoque GRASP como solución eficiente y adaptable, e inspiran futuras investigaciones en heurísticas más avanzadas para este problema.

Sergio Cavero

Phd in Artificial Intelligence

Sergio Cavero was born Madrid (Spain) on September 24, 1997. He graduated in Software Engineering from Universidad Politécnica de Madrid in 2019. During his undergraduate studies he made a stay at the University of Bradford (UK). In addition, he was awarded twice with the ‘Beca de Excelencia of the Comunidad de Madrid, and also awarded for the Best Final Degree Project. Later, he completed a Master’s Degree in Artificial Intelligence at the same university (UPM) obtaining awards for Best Academic Record (‘Premio José Cuena’) and Best Master’s Thesis. He academic results lend him be beneficiary of one of the ‘Ayudas Para la Formación de Profesorado Universitario (FPU)’, funded by the Spanish Government. He is currently carrying out his doctoral thesis at the Universidad Rey Juan Carlos, supervised by Professors Abraham Duarte and Eduardo G. Pardo. His main research interests focus on the interface among Computer Science, Artificial Intelligence and Operations Research. Most of his publications deal with the development of metaheuristics procedures for optimization problems modeled by graphs.

Isaac Lozano-Osorio

Phd in Artificial Intelligence

Isaac Lozano graduated with a double degree in Computer Engineering and Computer Engineering from the Universidad Rey Juan Carlos, where he was awarded the prize for the Best Final Project. Subsequently, he completed a Master in Artificial Intelligence Research (UIMP). His main research interests are focused on the interface between Computer Science, Artificial Intelligence and Operations Research. Most of his publications deal with the development of metaheuristic procedures for graph modeled optimization problems.