Passenger Simulation Models for Transit Scheduling and Facility Layout Planning in Airports

Simulating the movements of passengers on service systems has always been an interesting business problem. Unlike manufacturing systems, where processes and the movement of personnel follow predefined pathways, service systems like airports require a lot of information about customer movements and behaviors. In this work, we propose two simulation models to simulate passenger movement in airport systems. The first one is a discrete event simulation model, which models passengers and trains in an airport transit system. In the second model, we use the social force model, a microscopic agent-based model, to model the movement of passengers inside airport check-in facilities. Simulated annealing, along with the transit simulation model, is used to optimize the scheduling of trains to minimize waiting times and maximize occupancy. We consider the facility layout planning problem for the airport check-in area and use large language models to improve the layout. To evaluate the efficacy of the model, we use the social force model and space syntax analysis. Results indicate that the scheduling optimization can bring a 200% improvement, whereas the improved facility layout delivers a 2% improvement in the throughput.