In this paper, we propose a general energy function for a new neural model, the random neural model of Gelenbe. This model proposes a scheme of interaction between the neurons and not a dynamic equation of the system. We then apply this general energy function on different optimization problems: the graph partitionning problem and the minimum node coveting problem.
Jose, A. (1998). Definition of an energy function for the random neural to solve optimization problems. Neural Networks, 11(4), 731–737. https://doi.org/10.1016/S0893-6080(98)00020-3