Evolving Multi-level Graph Partitioning Algorithms
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Pope:2016:ieeeSSCI,
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author = "Aaron S. Pope and Daniel R. Tauritz and
Alexander D. Kent",
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booktitle = "2016 IEEE Symposium Series on Computational
Intelligence (SSCI)",
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title = "Evolving Multi-level Graph Partitioning Algorithms",
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year = "2016",
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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.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/SSCI.2016.7849930",
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month = dec,
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notes = "Also known as \cite{7849930}",
- }
Genetic Programming entries for
Aaron S Pope
Daniel R Tauritz
Alexander D Kent
Citations