Optimization of bus routes : case study of the University of Balamand

Abstract

Given the shortfall of reliable public transport systems in Lebanon, the high mobility expenses, the burden of traffic congestion and the adverse socio-environmental costs associated with it, the implementation of sustainable transportation networks is crucial. While Lebanon is known to have very high rates of car ownership, workers and students are currently seeking affordable public transport solutions. This paper proposes and investigates the optimization of the bus network for the University of Balamand, to provide convenient and affordable transportation for students and staff. The main aim is to maximize service coverage and minimize mobility costs, while considering traffic data. A mathematical model that solves this problem as a Multiple Traveling Salesman Problem (MTSP) by using the Genetic Algorithm (GA) is proposed, where further constraints such as minimum and maximum number of cities to be visited are explored. This optimization problem is also modeled and analyzed using Network Analyst in ArcGIS Pro. By leveraging traffic data in network analysis, data-driven decisions can be taken, leading to more reliable, cost-effective, and user-centric network infrastructures. ArcGIS Network Analyst is used in two scenarios in the investigation. In Scenario 1, three buses are used to minimize resources and promote operational efficiency, whereas four buses are used in Scenario 2 to follow the established routes. The optimized routes outperformed the established ones in terms of efficiency. For customized mobility planning, it is advised to take into account student locations and real-time traffic data. Buses should operate on a set timetable to improve efficiency and service. The limitations of the mathematical model include presuming a single depot and excluding the actual road network. Future study should concentrate on creating a bus timetable and real-time or historical traffic data should be added to overcome these restrictions. Reliability, effectiveness, and commuter experience would all improve as a result.