Title :
Solving the generalised quadratic assignment problem using a self-organising process
Author_Institution :
Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia
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;
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
DOI :
10.1109/ICNN.1995.488955
