Genetic Algorithms for Graph Partitioning and Incremental Graph Partitioning

  • Maini H
  • Mehrotra K
  • Mohan C
 et al. 
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Abstract

Partitioning graphs into equally large groups of nodes, minimizing
the number

of edges between different groups, is an extremely important problem
in parallel

computing. This paper presents genetic algorthims for suboptimal graph
partitioning,

with new crossover operators (KNUX, DKNUX) that leads to orders of
magnitude

improvement over traditional genetic operators in solution quality
and speed. Our

method can improve on good solutions previously obtained by using
other algorithms

or graph theoretic heuristics in minimizing the total communication
cost or the worst

case cost of communication for a single processor. We also extend
our algorithm to

Incremental Graph Partitioning problems, in which the graph structure
or system

properties changes with time.

Author-supplied keywords

  • Genetic algorithms
  • Graph partitioning

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Authors

  • H Maini

  • K Mehrotra

  • C Mohan

  • S Ranka

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