Title :
Solving ability of Hopfield Neural Network with scale-rule noise for QAP
Author :
Tada, Yoshifumi ; Uwate, Yoko ; Nishio, Yoshifumi
Author_Institution :
Dept. of Electr. & Electron. Eng., Tokushima Univ., Tokushima
Abstract :
One of the applications of neural network is solving combinatorial optimization problems. In our past study, the solving ability of the Hopfleld Neural Network with noise for quadratic assignment problem is investigated. However, even if we injected the noise to the network, the optimal solution cannot occasionally be found. In this study, we propose the method adding scale-rule noise to the Hopfleld Neural Network to achieve better performance. By computer simulations solving quadratic assignment problem, we evaluate the performance of the method.
Keywords :
Hopfield neural nets; mathematics computing; optimisation; Hopfield neural network; QAP; quadratic assignment problem; scale-rule noise; Chaos; Computer simulation; Hopfield neural networks; Logistics; Neural networks; Neurons; Noise level; Performance gain; Production facilities; Stochastic resonance;
Conference_Titel :
Circuits and Systems, 2008. ISCAS 2008. IEEE International Symposium on
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4244-1683-7
Electronic_ISBN :
978-1-4244-1684-4
DOI :
10.1109/ISCAS.2008.4541365