Name
Title | ||
|---|---|---|
Stochastic Functional Annealing as Optimization Technique: Application to the Traveling Salesman Problem with Recurrent Networks |
Abstract | ||
|---|---|---|
In this work, a new stochastic method for optimization problems is developed. Its theoretical bases guaranteeing the convergence of the method to a minimum of the objective function are presented, by using quite general hypotheses. Its application to recurrent discrete neural networks is also developed, focusing in the multivalued MREM model, a generalization of Hopfield's. In order to test the efficiency of this new method, we study the well-known Traveling Salesman Problem. Experimental results will show that this new model outperforms other techniques, achieving better results, even on average, than other methods. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74565-5_30 | KI |
Keywords | Field | DocType |
optimization technique,new model,objective function,stochastic functional annealing,new stochastic method,salesman problem,multivalued mrem model,general hypothesis,better result,recurrent networks,discrete neural network,new method,traveling salesman problem | Bottleneck traveling salesman problem,Convergence (routing),Mathematical optimization,Combinatorial optimization,Cross-entropy method,Travelling salesman problem,2-opt,Artificial neural network,Optimization problem,Mathematics | Conference |
Volume | ISSN | Citations |
4667 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Domingo López-Rodríguez | 1 | 55 | 9.24 |
| Enrique Mérida-Casermeiro | 2 | 30 | 5.80 |
| Gloria Galán-Marín | 3 | 108 | 9.64 |
| Juan M. Ortiz-De-Lazcano-Lobato | 4 | 13 | 3.00 |