Resumen
With the growth of cities, urban traffic has increased and traffic congestion has become a serious problem. Due to their characteristics, metro systems are one of the most used public transportation networks in big cities. So, optimization and planning of metro networks are challenges which governments must focus on. The objective of this study was to analyze Madrid metro network using graph theory. Through complex network theory, the main structural and topological properties of the network as well as robustness characteristics were obtained. Furthermore, to inspect these results, multivariate analysis techniques were employed, specifically HJ-Biplot. This analysis tool allowed us to explore relationships between centrality measures and to classify stations according to their centrality. Therefore, it is a multidisciplinary study that includes network analysis and multivariate analysis. The study found that closeness and eccentricity were strongly negatively correlated. In addition, the most central stations were those located in the city center, that is, there is a relationship between centrality and geographic location. In terms of robustness, a highly agglomerated community structure was found.