Transportation Networks & Network Mathematics
Transportation is not limited to roads, railways or vehicles. It is based on networks. Every shipment, commute and logistics chain depends on a system of connections between cities, terminals, ports and digital platforms. These transportation networks support trade, mobility and service availability throughout all society.
Understanding and developing these networks requires more than physical infrastructure or timetables. It requires a mathematical approach.
Network Mathematics in Transport Planning
Network mathematics, also known as graph theory models transportation systems using nodes and links. This enables the analysis of structure, flow, dependencies and performance across the system.
Key applications include:
- Route planning: Finding paths based on distance, time, cost, or constraints.
- Disruption analysis: Assessing the impact of road closures or other disturbances.
- Capacity planning: Identifying bottlenecks and evaluating system load.
- Infrastructure development: Comparing network configurations for new projects.
- Multimodal integration: Structuring transitions between road, rail, sea, and air transport.
Solving Practical Problems with Network Models
Transport planners and logistics operators face a range of operational and strategic questions that can be approached with network-based tools. For example:
- How can delivery routes be organized to minimize driving distance?
- Which terminals or links are most sensitive to delays or failures?
- Where should infrastructure investments be made to improve system performance?
- How can long-distance and regional networks be integrated for combined freight flows?
These types of questions require a structured representation of the transport system. Algorithms are then applied to identify paths, calculate flows, detect weaknesses or compare scenarios. This supports decision-making based on data and logic, rather than estimates alone.
Algorithms Used in Transportation Networks
If you are interested in learning more about the algorithms and wonder what are the most used in network planning. Here are several well-known algorithms are used in network-based transport planning:
- Dijkstra’s algorithm – Shortest path calculation between two nodes.
- Bellman-Ford algorithm – Pathfinding with the inclusion of negative weights.
- Floyd-Warshall algorithm – All-pairs shortest path computation for full-network accessibility.
- Ford-Fulkerson algorithm – Maximum flow estimation through a network, used in capacity analysis.
- Kruskal’s / Prim’s algorithms – Construction of minimum spanning trees for cost-effective network layouts.
- Centrality metrics (e.g., betweenness, degree) – Identification of critical nodes for investment or resilience planning.
These tools support various types of transport analysis, from routing to infrastructure planning and network resilience.
Looking Ahead: Network-Based Planning in the LOBRA Project
The development of transport systems requires not only understanding how networks operate today, but also how they can evolve. As part of the LOBRA project, we are applying network mathematics to explore how freight corridors function in practice, how transport modes are combined and how planning tools can support long-term logistics development.
Our ongoing work examines how transport chains are built, how decisions about modal shifts are made and how the structure of the network influences efficiency, reliability, and adaptability. This research aims to improve the understanding of logistics performance at regional and national levels.
By continuing to apply network-based approaches in real planning contexts, we contribute to the development of tools that help organizations and authorities make informed decisions about future transport infrastructure and operations.
Project number: 404191