Abstract
The Bi-Objective Multiple Row Equal Facility Layout Problem considers both quantitative and qualitative objectives that are very useful in many scenarios like the factory design. In this work, a new multi-objective GRASP approach is proposed which applies an ensemble of four different constructive methods followed by the combination of two local search procedures, improving the results from the state of the art. Due to the superiority of this proposal, a new dataset of larger problem instances is generated, providing detailed metrics of the obtained solutions.
Nicolás Rodríguez Uribe
Phd in Artificial Intelligence
Nicolás Rodríguez Uribe graduated with a degree in Computer Engineering from Universidad Rey Juan Carlos in 2015. Subsequently, he completed a Master’s Degree in Decision Systems Engineering in 2018 and obtained his Doctorate in Artificial Intelligence from the same university in 2022. His main research interests focus on heuristics and metaheuristics, combinatorial optimization, trajectory algorithms, genetic algorithms, and multi-objective problems. He is a member of the high-performance research group in optimization algorithms (GRAFO) at Universidad Rey Juan Carlos. Most of his publications deal with the development of heuristic and metaheuristic procedures to solve complex optimization problems.
Alberto Herrán González
Associate Professor
J. Manuel Colmenar
Full Professor
My research interests are focused on metaheuristics applied to optimization problems. I have worked on different combinatorial optimization problems applying trajectorial algorithms such us GRASP or VNS. Besides, I am very interested in applications of Grammatical Evolution, specifically in model and prediction domain, as alternative to machine learning approaches.