Conference paper accepted: Stochastic functional annealing as optimization technique: Application to the traveling salesman problem with recurrent networks

The work Stochastic functional annealing as optimization technique: Application to the traveling salesman problem with recurrent networks has been published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), (4667 LNAI), pp. 397-411.

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. © Springer-Verlag Berlin Heidelberg 2007.

For more details on this work, visit its own page.