Urban transportation systems, comprising critical elements such as light-speed trains, monorails, and underground metros, are the backbone of city infrastructure, facilitating the movement of millions of passengers daily. Ensuring the successful operation of these complex systems necessitates proper scheduling of trains across a diverse network of stations, a task that is both intricate and demanding. This research paper aims to optimize metro operations by employing advanced simulation software that allows for the comprehensive examination of various operational schedules, coupled with the ability to model and analyze passenger behavior and evaluate the conditions of the existing infrastructure. The research has several key objectives: enhancing train efficiency to improve overall system performance, increasing passenger comfort to boost public acceptance, reducing travel times to enhance competitiveness with other modes of transport, and curtailing operational costs to improve the economic viability of the metro system. To mitigate the ever-present congestion challenge and distribute passenger load more efficiently, the research proposes a novel approach that involves operating a subset of trains within specific sections of the railway rather than across the entire network. The simulation model considers parameters such as train and passenger arrival rates at each station, probable passenger destinations, and train capacities. The research provides valuable insights into the operation and optimization of metro systems and generates actionable recommendations for metro operators and policymakers. These insights and recommendations, when implemented, have the potential to transform urban transportation systems, streamline metro operations, and significantly enhance the commuting experience for passengers.