Genetic algorithm and graph partitioning

Thang Nguyen Bui, Byung Ro Moon

Research output: Contribution to journalArticle

245 Citations (Scopus)

Abstract

Hybrid genetic algorithms (GAs) for the graph partitioning problem are described. The algorithms include a fast local improvement heuristic. One of the novel features of these algorithms is the schema preprocessing phase that improves GAs' space searching capability, which in turn improves the performance of GAs. Experimental tests on graph problems with published solutions showed that the new genetic algorithms performed comparable to or better than the multistart Kernighan-Lin algorithm and the simulated annealing algorithm. Analyses of some special classes of graphs are also provided showing the usefulness of schema preprocessing and supporting the experimental results.

Original languageEnglish (US)
Pages (from-to)841-855
Number of pages15
JournalIEEE Transactions on Computers
Volume45
Issue number7
DOIs
StatePublished - Dec 1 1996

Fingerprint

Graph Partitioning
Genetic algorithms
Genetic Algorithm
Schema
Preprocessing
Multistart
Hybrid Genetic Algorithm
Simulated Annealing Algorithm
Graph in graph theory
Simulated annealing
Heuristics
Experimental Results

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics

Cite this

Bui, Thang Nguyen ; Moon, Byung Ro. / Genetic algorithm and graph partitioning. In: IEEE Transactions on Computers. 1996 ; Vol. 45, No. 7. pp. 841-855.
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Genetic algorithm and graph partitioning. / Bui, Thang Nguyen; Moon, Byung Ro.

In: IEEE Transactions on Computers, Vol. 45, No. 7, 01.12.1996, p. 841-855.

Research output: Contribution to journalArticle

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