DocumentCode
296135
Title
Solving the generalised quadratic assignment problem using a self-organising process
Author
Smith, Kate
Author_Institution
Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia
Volume
4
fYear
1995
fDate
Nov/Dec 1995
Firstpage
1876
Abstract
A novel self-organising neural network is presented which is designed to solve generalised quadratic assignment problems. Details of the architecture, algorithm, and convergence properties are provided. The method is demonstrated using a small numerical example from the literature, and conclusions are drawn
Keywords
combinatorial mathematics; convergence; minimisation; self-organising feature maps; convergence properties; generalised quadratic assignment problem; self-organising process; Cities and towns; Constraint optimization; Convergence; Cost function; Geometry; Hypercubes; Neural networks; Transportation; Traveling salesman problems; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.488955
Filename
488955
Link To Document