1. A computer-implemented method for managing structures in stochastic networks comprising: creating a general analytical model for a stochastic network; decomposing the general analytic model into a set of one or more decomposed analytic models; generating an optimization problem based on capacities and a topological configuration of network structures in each of the one or more decomposed analytic models; iteratively obtaining an approximate solution to the optimization problem by: specifying an initial iterate value for the optimization variable of a capacity and a network structure to be optimized; evaluating the network at a current iterate to determine the parameters of a functional form of each decomposed analytical model at the current iterate; jointly optimizing the decomposed analytical models with the determined parameters to obtain a next iterate of the optimization variables of the capacities and network structures; determining whether the next iterate meets a pre-determined stopping criteria, and one of: returning the current iterate as values for the capacities and network structures as an approximate solution if the next iterate meets the pre-determined stopping criteria; or setting new iterate values for optimization variables of the capacities and the network structures to be optimized as current iterate values and repeating the evaluating, jointly optimizing and stopping criteria determining at the current iterate values to determine the parameters of the functional form of each decomposed analytic model; and determining the capacities and the topological configuration of network structures for the stochastic network based on the approximate solution, wherein a programmed hardware processor device is configured to perform one or more of the creating, decomposing, generating, specifying, evaluating, jointly optimizing and stopping criteria determining.