A Neural Network Parallel Algorithm for Meeting Schedule Problems

Kazuhiro Tsuchiya, Yoshiyasu Takefuji

Research output: Contribution to journalArticle

4 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 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 languageEnglish
Pages (from-to)205-213
Number of pages9
JournalApplied Intelligence
Volume7
Issue number3
Publication statusPublished - 1997

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Parallel algorithms
Neural networks
Computational complexity

Keywords

  • Meeting schedule
  • Neural network
  • Parallel algorithm
  • Scheduling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence

Cite this

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

In: Applied Intelligence, Vol. 7, No. 3, 1997, p. 205-213.

Research output: Contribution to journalArticle

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