Neural network parallel algorithm for meeting schedule problems

Kazuhiro Tsuchiya, Yoshiyasu Takefuji, Ken ichi Kurotani, Kunio Wakahara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

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 languageEnglish
Title of host publicationIEEE Region 10 Annual International Conference, Proceedings/TENCON
PublisherIEEE
Pages173-177
Number of pages5
Volume1
Publication statusPublished - 1996
Externally publishedYes
EventProceedings of the 1996 IEEE Region 10 TENCON - Digital Signal Processing Applications Conference. Part 2 (of 2) - Perth, Aust
Duration: 1996 Nov 261996 Nov 29

Other

OtherProceedings of the 1996 IEEE Region 10 TENCON - Digital Signal Processing Applications Conference. Part 2 (of 2)
CityPerth, Aust
Period96/11/2696/11/29

Fingerprint

Parallel algorithms
Neural networks
Computational complexity

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Tsuchiya, K., Takefuji, Y., Kurotani, K. I., & Wakahara, K. (1996). Neural network parallel algorithm for meeting schedule problems. In 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.

IEEE Region 10 Annual International Conference, Proceedings/TENCON. Vol. 1 IEEE, 1996. p. 173-177.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Tsuchiya, K, Takefuji, Y, Kurotani, KI & Wakahara, K 1996, Neural network parallel algorithm for meeting schedule problems. in 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.
Tsuchiya K, Takefuji Y, Kurotani KI, Wakahara K. Neural network parallel algorithm for meeting schedule problems. In IEEE Region 10 Annual International Conference, Proceedings/TENCON. Vol. 1. IEEE. 1996. p. 173-177
Tsuchiya, Kazuhiro ; Takefuji, Yoshiyasu ; Kurotani, Ken ichi ; Wakahara, Kunio. / Neural network parallel algorithm for meeting schedule problems. IEEE Region 10 Annual International Conference, Proceedings/TENCON. Vol. 1 IEEE, 1996. pp. 173-177
@inproceedings{01411b101ad043ceae9e9ff822059e6f,
title = "Neural network parallel algorithm for meeting schedule problems",
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.",
author = "Kazuhiro Tsuchiya and Yoshiyasu Takefuji and Kurotani, {Ken ichi} and Kunio Wakahara",
year = "1996",
language = "English",
volume = "1",
pages = "173--177",
booktitle = "IEEE Region 10 Annual International Conference, Proceedings/TENCON",
publisher = "IEEE",

}

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

VL - 1

SP - 173

EP - 177

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

PB - IEEE

ER -