Neural network parallel algorithm for meeting schedule problems

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

Research output: Contribution to conferencePaperpeer-review

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
Pages173-177
Number of pages5
Publication statusPublished - 1996 Dec 1
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

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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