Primal and dual neural networks for shortest-path routing

Jun Wang

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)

Abstract

This paper presents two recurrent neural networks for solving the shortest path problem. Simplifying the architecture of a recurrent neural network based on the primal problem formulation, the first recurrent neural network called the primal routing network has less complex connectivity than its predecessor. Based on the dual problem formulation, the second recurrent neural network called the dual routing network has even much simpler architecture. While being simple in architecture, the primal and dual routing networks are capable of shortest-path routing like their predecessor.

Original languageEnglish
Pages (from-to)864-869
Number of pages6
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans.
Volume28
Issue number6
DOIs
Publication statusPublished - 1998
Externally publishedYes

Keywords

  • Neural networks
  • Optimization
  • Shortest path problem

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