A Multi‐Objective Optimization Framework for Locating Metro Stations by Integrating Travel Demand, Accessibility, and Land Use Intensity

Transit‐Oriented Development (TOD) strategies help to achieve sustainable transportation and vibrant communities. The selection of suitable locations for metro stations plays a fundamental role in implementing TOD planning. However, current research predominantly focuses on evaluating existing metro stations, often overlooking the critical task of optimally locating new ones. This study proposes a multi‐objective optimization framework for locating urban metro stations based on the concept of TOD, which takes three key dimensions: travel demand, functional accessibility, and land use intensity into consideration. We develop an iterative optimization process by combining a greedy search method with an elite fast non‐dominated sorting genetic algorithm (NSGA‐II) to search for solutions that satisfy the three objectives. The proposed model is validated through a case study in Xi'an, China, where its feasibility is assessed by designing various scenarios. The results indicate that the model can effectively identify optimal locations for metro stations under multiple objectives. Therefore, the proposed method can be used to assist urban planners in identifying suitable locations for transit stations.