Comparative Performance Analysis of Major Indian Metropolitan Metro Rail Systems: Multi-Criteria Decision Analysis (MCDA) Approach

India’s rapid urbanisation has catalysed significant investment in metro rail infrastructure across its major cities. Evaluating these systems demands methods that capture both operational performance and the structural properties of the networks themselves. In response to this need, and in alignment with recent advances in transport network analysis — notably the application of constrained centrality measures (degree, betweenness, closeness, and eigenvector centrality) as proposed in “Centrality analysis for railway network planning” — this paper augments a classical multi-criteria framework with graph-theoretic network performance indicators. We present a comprehensive comparative analysis of seven major Indian metropolitan metro systems — Delhi, Mumbai, Bengaluru (Namma Metro), Chennai, Kolkata, Hyderabad, and Nagpur — to determine the best-performing network. Using an extended Weighted Composite Scoring Framework (WCSF), we evaluate each system across seven performance dimensions: (1) network size and coverage, (2) ridership and demand fulfilment, (3) operational efficiency, (4) technical advancement, (5) financial sustainability, (6) environmental performance, and (7) transport network centrality — capturing betweenness centrality of interchange nodes and closeness centrality of the station graph. Network centrality metrics are derived from the L-space and P-space graph representations of each metro topology, with time-constrained weighted variants applied to reflect real-world service headways. Our findings identify the Delhi Metro as the overall best-performing system (PI = 8.92), driven by its unparalleled network coverage (374.47 km), highest ridership (6.46 million daily), strongest betweenness centrality at key interchange nodes, and longest operational history. Bengaluru’s Namma Metro ranks second (PI = 7.41), excelling in ridership density, closeness centrality relative to its network size, and year-on-year growth trajectory. The integration of constrained centrality measures into the performance framework reveals that topological connectivity — particularly the role of hub stations in sustaining network flow under disruption — is a significant, previously underweighted differentiator among Indian metro systems. The paper concludes with policy recommendations for under-performing systems and identifies key success drivers, including centrality-informed station planning, replicable across emerging metro cities in India.