### Abstract

A parallel algorithm for solving meeting schedule problems is presented in this paper where the problem is NP-complete. The proposed system is composed of two maximum neural networks which interact with each other. One is an M×S neural network to assign meetings to available time slots on a timetable where M and S are the number of meetings and the number of time slots, respectively. The other is an M×P neural network to assign persons to the meetings where P is the number of persons. The simulation results show that the state of the system always converges to one of the solutions and that the solution quality of the proposed algorithm does not degrade with the problem size.

Original language | English |
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Title of host publication | IEEE Region 10 Annual International Conference, Proceedings/TENCON |

Publisher | IEEE |

Pages | 173-177 |

Number of pages | 5 |

Volume | 1 |

Publication status | Published - 1996 |

Externally published | Yes |

Event | Proceedings of the 1996 IEEE Region 10 TENCON - Digital Signal Processing Applications Conference. Part 2 (of 2) - Perth, Aust Duration: 1996 Nov 26 → 1996 Nov 29 |

### Other

Other | Proceedings of the 1996 IEEE Region 10 TENCON - Digital Signal Processing Applications Conference. Part 2 (of 2) |
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City | Perth, Aust |

Period | 96/11/26 → 96/11/29 |

### Fingerprint

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*IEEE Region 10 Annual International Conference, Proceedings/TENCON*(Vol. 1, pp. 173-177). IEEE.

**Neural network parallel algorithm for meeting schedule problems.** / Tsuchiya, Kazuhiro; Takefuji, Yoshiyasu; Kurotani, Ken ichi; Wakahara, Kunio.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*IEEE Region 10 Annual International Conference, Proceedings/TENCON.*vol. 1, IEEE, pp. 173-177, Proceedings of the 1996 IEEE Region 10 TENCON - Digital Signal Processing Applications Conference. Part 2 (of 2), Perth, Aust, 96/11/26.

}

TY - GEN

T1 - Neural network parallel algorithm for meeting schedule problems

AU - Tsuchiya, Kazuhiro

AU - Takefuji, Yoshiyasu

AU - Kurotani, Ken ichi

AU - Wakahara, Kunio

PY - 1996

Y1 - 1996

N2 - A parallel algorithm for solving meeting schedule problems is presented in this paper where the problem is NP-complete. The proposed system is composed of two maximum neural networks which interact with each other. One is an M×S neural network to assign meetings to available time slots on a timetable where M and S are the number of meetings and the number of time slots, respectively. The other is an M×P neural network to assign persons to the meetings where P is the number of persons. The simulation results show that the state of the system always converges to one of the solutions and that the solution quality of the proposed algorithm does not degrade with the problem size.

AB - A parallel algorithm for solving meeting schedule problems is presented in this paper where the problem is NP-complete. The proposed system is composed of two maximum neural networks which interact with each other. One is an M×S neural network to assign meetings to available time slots on a timetable where M and S are the number of meetings and the number of time slots, respectively. The other is an M×P neural network to assign persons to the meetings where P is the number of persons. The simulation results show that the state of the system always converges to one of the solutions and that the solution quality of the proposed algorithm does not degrade with the problem size.

UR - http://www.scopus.com/inward/record.url?scp=0030315019&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0030315019&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0030315019

VL - 1

SP - 173

EP - 177

BT - IEEE Region 10 Annual International Conference, Proceedings/TENCON

PB - IEEE

ER -