Neural nets model for combinatorial optimization

Neural nets are a strongly inderdisciplinary research field. Therefore it seems useful to perform a synthesis of the various models which have been proposed in recent years, with an outline of the main results obtained. This review is devoted to neural models for combinatorial optimization, and some classification criteria are proposed for such models. The comparison between models is aimed to show similarities and differences between them. The explanation is kept on a general level in order to favour the synthetic approach over the more usual analytical one.