A real -time solution for the traveling salesman problem using a boolean neural network

Shirish Bhide, Nigel John, M. R. Kabuka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper, we have 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 is proposed for solving this problem. The simulation results have been found to be comparable to the Simulated Annealing algorithm, which is used as a test base. The results show a better variance as compared to Simulated Annealing. The modified Boolean Neural Network implementation involves lesser hardware complexity, good noise immunity and faster circuitry. This is very important in real-time systems and commercial job scheduling applications.

Original languageEnglish (US)
Title of host publication1993 IEEE International Conference on Neural Networks, ICNN 1993
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1096-1103
Number of pages8
ISBN (Electronic)0780309995
DOIs
StatePublished - Jan 1 1993
EventIEEE International Conference on Neural Networks, ICNN 1993 - San Francisco, United States
Duration: Mar 28 1993Apr 1 1993

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
Volume1993-January
ISSN (Print)1098-7576

Other

OtherIEEE International Conference on Neural Networks, ICNN 1993
CountryUnited States
CitySan Francisco
Period3/28/934/1/93

ASJC Scopus subject areas

  • Software

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