A new approach for the network development of an alternative rail transit system

It is argued that an optimally designed and built rail track network infrastructure enables effective passenger demand management through route planning techniques. In contrast, a poorly designed network leads to inefficient demand management. Developing a robust network plan for an alternative rail transit system that adapts to fluctuating demand is a critical challenge in transportation planning. This research presents a novel methodology for designing a rail network that optimally balances demand, cost, and future scalability. The methodology integrates a demand-based network using population gravity models and a cost-efficient network derived from the minimum spanning tree theorem. These two networks are superimposed to identify links that satisfy both demand and cost-efficiency criteria. An iterative process is then applied to minimize journey lengths and optimize overall network performance. The proposed methodology was applied to the Gampaha District in Sri Lanka, demonstrating its effectiveness in designing a cost-efficient alternative rail network. The results show that the network not only meets current transportation needs but also reduces sensitivity to future demand variations. Key outcomes include a reduction in network development costs by prioritizing high-demand and low-cost connections and an overall improvement in travel efficiency, with journey lengths significantly minimized. This approach provides a strategic framework for policymakers, enabling scalable and cost-effective transport solutions tailored to regional needs.