Evolving Multi-level Graph Partitioning Algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Pope:2016:ieeeSSCI,

• author = "Aaron S. Pope and Daniel R. Tauritz and Alexander D. Kent",
• booktitle = "2016 IEEE Symposium Series on Computational Intelligence (SSCI)",
• title = "Evolving Multi-level Graph Partitioning Algorithms",
• year = "2016",
• abstract = "Optimal graph partitioning is a foundational problem in computer science, and appears in many different applications. Multi-level graph partitioning is a state-of-the-art method of efficiently approximating high quality graph partitions. In this work, genetic programming techniques are used to evolve new multi-level graph partitioning heuristics that are tailored to specific applications. Results are presented using these evolved partitioners on traditional random graph models as well as a real-world computer network data set. These results demonstrate an improvement in the quality of the partitions produced over current state-of-the-art methods.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/SSCI.2016.7849930",
• month = dec,
• notes = "Also known as \cite{7849930}",

}

Genetic Programming entries for Aaron S Pope Daniel R Tauritz Alexander D Kent

Citations