Utilizing Discrete Event Simulation to Optimize Headway Times in a Light Rail Transit System

Due to recent urbanization and population growth in cities, the passenger transport system is faced with significant congestion and delay problems. In particular, to handle peak-time passenger traffic, railway public transport systems are operated with more frequent trips during the peak hours, and less-frequent train interarrivals are scheduled during off-peak hours to increase the total system utilization. This study proposes a simulation methodology for optimizing the trips of a metro line with variable passenger traffic. A microsimulation model was constructed using the Arena software to create an experimental medium for the optimization phase. The discrete-event simulation concept was utilized for the model building. The passenger flow and train arrival rates were the main input parameters obtained from the passenger origin-destination station matrix and train arrival data. The model was coupled with the artificial bee colony algorithm for determining the optimized train time headways. The optimization study resulted in a decrease of 27.5% and 25.5%in the total number of daily train trips for the normal and increased train capacity scenarios under a zero failed boarding policy. The results of the study were also compared with the literature findings which are discussed in detail.