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Optimal algorithms and data structures for decomposing graphs by small cuts and separators

Project description

Linear-time algorithms to solve fundamental graph problems

Real-world systems like road networks and social networks can be represented as graphs – structures made of points (vertices) connected by lines (edges). Solving problems on graphs, such as finding weak points or breaking them into smaller parts, is crucial in computer science. However, some fundamental problems still lack optimal solutions. With the support of the Marie Skłodowska-Curie Actions programme, the KCONN project aims to create optimal, linear-time algorithms for key graph challenges, such as identifying small edge cuts and calculating treewidth – a measure of graph complexity. By combining new techniques from structural graph theory, the proposed study could help solve long-standing challenges and advance the field of graph algorithms significantly.

Objective

Graphs are structures consisting of vertices (points) and edges (lines connecting pairs of points). Graphs can model systems such as road networks (intersections connected by roads), social networks (people connected by friendships), and the internet (computers connected by data links). The design of efficient algorithms for processing graphs is a classic area in computer science. However, there are still fundamental graph problems for which optimal algorithms remain undiscovered.

This project aims to design optimal algorithms and data structures for solving graph problems related to finding small cuts or separators and decomposing graphs accordingly. A basic example of a graph problem where I aim to advance the state-of-the-art is: Given a graph, determine whether it can be disconnected by removing at most 10 edges. The best-known algorithm runs in near-linear O(n log n + m) time, while the goal of this project is to obtain a linear-time O(n+m) algorithm, which is optimal. The specific number 10 is not important; rather, the goal is to develop a linear-time algorithm for any fixed value, in the spirit of parameterized algorithms.

The research objectives are (1) to develop a linear-time algorithm for computing the k-edge-connected components of a graph, (2) to create an improved dynamic data structure for treewidth, and (3) to design a linear-time preprocessing algorithm for computing treewidth. Objective (1) addresses a long-standing open problem in graph algorithms, while objectives (2) and (3) will significantly advance the state-of-the-art in key problems within parameterized algorithms. I believe I have identified a feasible approach to tackling these problems, introducing new techniques from structural graph theory into algorithm design.

Solving a key open problem in graph algorithms using tools from parameterized algorithms and structural graph theory will unify these fields and expand my professional network, significantly enhancing my career prospects.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

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

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Call for proposal

(opens in new window) HORIZON-MSCA-2024-PF-01

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Coordinator

KOBENHAVNS UNIVERSITET
Net EU contribution
€ 247 553,28
Address
NORREGADE 10
1165 KOBENHAVN
Denmark
Region
Danmark Hovedstaden Byen København
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data