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Geometric algorithms for transport network graphs

Project description

Expanding the potential of phi-low-density graphs

Transportation network analysis is a flourishing field of research and application, but transport network graphs face challenges in accurately representing real-world transport networks due to specialised and restrictive graph classes. Phi-low-density graphs, a type of geometric graph class, do a better job of capturing the characteristics of real-world transportation networks. However, their properties are not well understood, impeding development of specialised algorithms. With the support of the Marie Skłodowska-Curie Actions (MSCA) programme, the GA-TNG project aims to build fundamental structures for phi-low-density graphs and design provably efficient specialised algorithms for them. It will thus meet the need for a simple and versatile graph class that accurately represents a wide variety of real-world transport networks.

Objective

Graphs have been used to analyse transport networks for hundreds of years. However, graphs are general structures and many graph algorithms are very slow. Specialised algorithms are much more efficient but can only be applied to restricted graph classes. Transport network graphs suffer from a lack of efficient specialised algorithms, since most graph classes are too restrictive and do not accurately represent real-world transport networks.

Recent developments have led to geometric graph classes that are tailored to real-world transport networks. One of these geometric graph classes, phi-low-density graphs, captures the property that there are more connections between geographically nearby nodes than geographically distant ones. Unfortunately, the fundamental properties of phi-low-density graphs are not well understood, which has prevented the development of a wide range of specialised algorithms.

My objective is to fill the acute need for a simple and versatile graph class that accurately represents real-world transport networks. My research will allow experts to finally harness the power of specialised algorithms on a wide range of important transport network problems. I will achieve my objectives through two sub-objectives: (1) To build fundamental structures for phi-low-density graphs, and (2) To design provably efficient specialised algorithms for phi-low-density graphs.

I will be support by my host institution (University of Copenhagen), my host group (Basic Algorithms Research Copenhagen), my primary supervisor (Mikkel Abrahamsen), and my secondary supervisor (Rasmus Pagh).

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2023-PF-01

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Coordinator

KOBENHAVNS UNIVERSITET
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 230 774,40
Address
NORREGADE 10
1165 KOBENHAVN
Denmark

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Region
Danmark Hovedstaden Byen København
Activity type
Higher or Secondary Education Establishments
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Total cost

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