Solving the assignment problem using continuous-time and discrete-time improved dual networks

Xiaolin Hu, Jun Wang

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

The assignment problem is an archetypal combinatorial optimization problem. In this brief, we present a continuous-time version and a discrete-time version of the improved dual neural network (IDNN) for solving the assignment problem. Compared with most assignment networks in the literature, the two versions of IDNNs are advantageous in circuit implementation due to their simple structures. Both of them are theoretically guaranteed to be globally convergent to a solution of the assignment problem if only the solution is unique.

Original languageEnglish
Article number6155745
Pages (from-to)821-827
Number of pages7
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume23
Issue number5
DOIs
Publication statusPublished - 2012
Externally publishedYes

Keywords

  • Analog circuits
  • assignment problem
  • linear programming
  • quadratic programming
  • sorting problem

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