A Dual Neural Network Scheme for Solving the Assignment Problem. (2nd February 2016)
- Record Type:
- Journal Article
- Title:
- A Dual Neural Network Scheme for Solving the Assignment Problem. (2nd February 2016)
- Main Title:
- A Dual Neural Network Scheme for Solving the Assignment Problem
- Authors:
- Nazemi, Alireza
Ghezelsofla, Ozra - Abstract:
- Abstract: The assignment problem is an archetypal combinatorial optimization problem. This paper presents a neural network based on a dynamic model for solving the assignment problem. The main idea is to replace the assignment problem with a linear programming problem. On the basis of the Karush–Kuhn–Tucker optimality conditions, the equilibrium point of the proposed neural network is proved to be equivalent to the optimal solution of the original problem. It is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact optimal solution of the assignment problem. Block diagram of the proposed model is given. Several illustrative examples are provided to show the feasibility and the efficiency of the proposed method in this paper.
- Is Part Of:
- Computer journal. Volume 60:Number 3(2017)
- Journal:
- Computer journal
- Issue:
- Volume 60:Number 3(2017)
- Issue Display:
- Volume 60, Issue 3 (2017)
- Year:
- 2017
- Volume:
- 60
- Issue:
- 3
- Issue Sort Value:
- 2017-0060-0003-0000
- Page Start:
- 431
- Page End:
- 443
- Publication Date:
- 2016-02-02
- Subjects:
- neural network -- assignment problem -- shortest path problem -- linear programming -- convergent -- stability
Computers -- Periodicals
005.1 - Journal URLs:
- http://comjnl.oxfordjournals.org/ ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/comjnl/bxw003 ↗
- Languages:
- English
- ISSNs:
- 0010-4620
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.060000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21744.xml