A proposal of neuron filter: A constraint resolution scheme of neural networks for combinatorial optimization problems

Yoichi Takenaka, Nobuo Funabiki, Teruo Higashino

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

A constraint resolution scheme in the Hopfield-type neural network named Neuron Filter is presented for efficiently solving combinatorial optimization problems. The neuron filter produces an output that satisfies the constraints of the problem as best as possible according to both neuron inputs and outputs. This paper defines the neuron filter and shows its introduction into existing neural networks for N-queens problems and FPGA board-level routing problems. The performance is evaluated through simulations where the results show that our neuron filter improves the searching capability of the neural network with the shorter computation time.

Original languageEnglish
Pages (from-to)1815-1822
Number of pages8
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE83-A
Issue number9
Publication statusPublished - 2000
Externally publishedYes

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Keywords

  • Board-level routing problem
  • Combinatorial optimization problem
  • Hopfileld-type neural network
  • N-queens problem
  • Neuron filter

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Hardware and Architecture
  • Information Systems

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