This thesis surveys major algorithmic developments for computing treewidth and discusses the compression and improvement paradigm developed in the 1990s, especially in the work of Bodlaender and Kloks, and Bodlaender and Hagerup.
This work applies TDP to enhance algorithms across diverse paradigms, including evolutionary search, greedy heuristics, and graph-neural-network-based heuristics, and shows that TDP significantly improves performance over the original methods.
Jialiang Li, Aneta Neumann, Frank Neumann et al.· Proceedings of the Thirty-Fi...· 1 citation
Tree-encoded partitionings of graphs are fundamental tools for the decomposition and approximation of graph signals. For the efficient approximation of such graph signals, we develop strategies based on $hp$-refinement by combining domain decomposition with an improved local approximation using polynomials of higher de...
This work generalizes the concepts of graph search trees by allowing every preceding neighbor of a vertex to be the parent, and presents NP-completeness proofs for most searches.
A unified Parallel Evolutionary Algorithm Framework (PEAF) is proposed, which combines structure-inheriting crossover operators, a hierarchical mutation mechanism based on the Multiple Mutation Heuristic and the Auxiliary Cut Mutation Heuristic, and a diversity-preserving selection strategy.
A simple unified framework is given that solves all these problems using only indegrees and completely characterises the class of problems that is determined by the indegree information: problems whose answers are invariant under cycle reversals.
Prantar Ghosh, Sahil Kuchlous, Shravan Mehra et al.· Embedded Systems and Applica...· 0 citations
