### 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 x 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 x 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. Our empirical study shows that the solution quality of the proposed algorithm does not degrade with the problem size.

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

Pages (from-to) | 205-213 |

Number of pages | 9 |

Journal | Applied Intelligence |

Volume | 7 |

Issue number | 3 |

Publication status | Published - 1997 |

### Fingerprint

### Keywords

- Meeting schedule
- Neural network
- Parallel algorithm
- Scheduling

### ASJC Scopus subject areas

- Control and Systems Engineering
- Artificial Intelligence

### Cite this

*Applied Intelligence*,

*7*(3), 205-213.

**A Neural Network Parallel Algorithm for Meeting Schedule Problems.** / Tsuchiya, Kazuhiro; Takefuji, Yoshiyasu.

Research output: Contribution to journal › Article

*Applied Intelligence*, vol. 7, no. 3, pp. 205-213.

}

TY - JOUR

T1 - A Neural Network Parallel Algorithm for Meeting Schedule Problems

AU - Tsuchiya, Kazuhiro

AU - Takefuji, Yoshiyasu

PY - 1997

Y1 - 1997

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 x 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 x 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. Our empirical study shows 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 x 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 x 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. Our empirical study shows that the solution quality of the proposed algorithm does not degrade with the problem size.

KW - Meeting schedule

KW - Neural network

KW - Parallel algorithm

KW - Scheduling

UR - http://www.scopus.com/inward/record.url?scp=0031189591&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031189591&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0031189591

VL - 7

SP - 205

EP - 213

JO - Applied Intelligence

JF - Applied Intelligence

SN - 0924-669X

IS - 3

ER -