Design and Presentation of an Approach to Improve the Tehran Metro Comprehensive Traffic System and Retrieve Timetables in the Disturbance Conditions Using a Robust Optimization Method

The Tehran Metro is usually subject to undesirable disruptions that can cause minor, major and sometimes unavoidable deviations from the original timetables. Based on the principles of disruption management, the Tehran Metro network solutions eliminate distortions such as train delays, dispatch cancellations, and passenger congestion through an intelligence-comprehensive traffic system. Considering the size and scope of Tehran metro lines, a computational solution according to the dimensions of problem solving approaches is required to achieve optimal decision making. One model presented in this research is an event-activity network to improve the comprehensive metro traffic management software. The research results show that the establishment of optimization models in the comprehensive metro system increases the success rate of operational results and the probability of traffic controller's decisions in the justified set of problem solutions. Thus, robust optimization methods can meaningfully improve the overall productivity index of subway lines and expand the capacity level of the subway network. In the present research, an attempt was made to estimate the ratio of the active trains on the line sections and the maximum possible number of trains. Especially during peak hours and taking into account the innovative structures. The capacity of trains in Tehran Metro's comprehensive system for creating the timetable is increased. In case of disruptions, it returns to normal conditions. Therefore, in the face of complications caused by multiple passenger dispatches, a neighborhood search algorithm was used to analyze passenger demand and to improve system.