Burning Graphs Through Farthest-First Traversal
Abstract
Domain fit: Niche / domain-specific · No strong AI-core implementation/artifact signals were detected from current providers.
Graph burning is a process to determine the spreading of information in a graph. If a sequence of vertices burns all the vertices of a graph by following the graph burning process, then such a sequence is known as a burning sequence. The graph burning problem consists in finding a minimum length burning sequence for a given graph. The solution to this NP-hard combinatorial optimization problem helps quantify a graph’s vulnerability to contagion. This paper introduces a simple farthest-first traversal-based approximation algorithm for this problem over arbitrary graphs. We refer to this proposal as the Burning Farthest-First (BFF) algorithm. BFF runs in <inline-formula> <tex-math notation="LaTeX">$O(n^{3})$ </tex-math></inline-formula> steps and has a tight approximation factor of <inline-formula> <tex-math notation="LaTeX">$3-2/b(G)$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$b(G)$ </tex-math></inline-formula> is the size of an optimal solution. The main attribute of BFF is that it has a better approximation factor than the state-of-the-art approximation algorithms for arbitrary graphs, which report an approximation factor of 3. Despite being simple, BFF proved practical when tested over some benchmark datasets.
Results and benchmarks
Graph burning is a process to determine the spreading of information in a graph.
Benchmark evidence is limited
Evidence graph: 2 refs, 1 links.
Utility signals: depth 60/100, grounding 58/100, status medium.
Implementation
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Reproduction readiness
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Validation caveat
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Research context
15
Citations
30
References
Tasks
Graph traversal, Tree traversal, Combinatorics, Graph, Sequence (biology), Benchmark (surveying), Computer science
Methods
Approximation algorithm, Algorithm
Domains
Discrete mathematics, Mathematics, Computational Theory and Mathematics
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