An evolutionary neural network approach for module orientation problems

Nobuo Funabiki, Junji Kitamichi, Seishi Nishikawa

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


A novel neural network approach called "Evolutionary Neural Network (ENN)" is presented for the module orientation problem. The goal of this NP-complete problem is to minimize the total wire length by flipping circuit modules with respect to their vertical and/or horizontal axes of symmetry. In order to achieve high quality VLSI systems, it is strongly desired to solve the problem as quickly as possible in the design cycle. Based on the concept of the genetic algorithm, the evolutionary initialization scheme on neuron states is introduced so as to provide a high quality solution within a very short time. The performance of ENN is compared with three heuristic algorithms through simulations on 20 examples with up to 500 modules. The results show that ENN can find the best solutions in the shortest time.

Original languageEnglish
Pages (from-to)849-855
Number of pages7
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Issue number6
Publication statusPublished - 1998
Externally publishedYes


  • Evolutionary initialization scheme
  • Module orientation
  • NP-complete
  • Neural network
  • VLSI design

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


Dive into the research topics of 'An evolutionary neural network approach for module orientation problems'. Together they form a unique fingerprint.

Cite this