A Boolean Neural Network Approach for the Traveling Salesman Problem

Shirish Bhide, Nigel John, M. R. Kabuka

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


It is shown that the Boolean neural network can be used to solve NP-complete problems. The problem under consideration is the traveling salesman problem. The Boolean neural network has been modified to include the iterative procedure for solving combinatorial optimization problems. An architecture that utilizes this modified Boolean neural network (MBNN) is proposed for solving this problem. The simulation results have been found to be comparable to the simulated annealing algorithm (SAA), which is used as a test base. The MBNN implementation involves low hardware complexity, good noise immunity, and fast circuitry. This is very important in real-time systems and commercial job scheduling applications.

Original languageEnglish (US)
Pages (from-to)1271-1278
Number of pages8
JournalIEEE Transactions on Computers
Issue number10
StatePublished - Oct 1993

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics


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