### Abstract

We present new decomposition heuristics for finding the optimal solution for the maximum-weight connected graph problem, which is known to be NP-hard. Previous optimal algorithms for solving the problem decompose the input graph into subgraphs using heuristics based on node degree. We propose new heuristics based on betweenness centrality measures, and show through computational experiments that our new heuristics tend to reduce the number of subgraphs in the decomposition, and therefore could lead to the reduction in computational time for finding the optimal solution. The method is further applied to analysis of biological pathway data.

Original language | English |
---|---|

Title of host publication | Discovery Science - 12th International Conference, DS 2009, Proceedings |

Pages | 465-472 |

Number of pages | 8 |

DOIs | |

Publication status | Published - 2009 Nov 16 |

Event | 12th International Conference on Discovery Science, DS 2009 - Porto, Portugal Duration: 2009 Oct 3 → 2009 Oct 5 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
---|---|

Volume | 5808 LNAI |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

### Other

Other | 12th International Conference on Discovery Science, DS 2009 |
---|---|

Country | Portugal |

City | Porto |

Period | 09/10/3 → 09/10/5 |

### ASJC Scopus subject areas

- Theoretical Computer Science
- Computer Science(all)

## Fingerprint Dive into the research topics of 'Better decomposition heuristics for the maximum-weight connected graph problem using betweenness centrality'. Together they form a unique fingerprint.

## Cite this

*Discovery Science - 12th International Conference, DS 2009, Proceedings*(pp. 465-472). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5808 LNAI). https://doi.org/10.1007/978-3-642-04747-3_40