We present a dynamic multicommodity minimum cost network flow problem with storage at the nodes and optimal supply for modeling operations within a logistics network. The model can be used to evaluate critical business decisions such as the amount of required resources for storage transportation as well as optimal supply policies. A generator for test instances was written in order to evaluate the performance of the different solution strategies. Using a number of differently sized randomly generated problem instances we compare the execution time and the memory demand of two methods for solving the problem. The first is solving the whole problem formulation directly using general purpose linear programming solvers implemented in IBM Ilog CPLEX. In the second approach we attempt to split the model into two parts and link them together in an optimization network. We analyze the quality of the link and propose possibilities to improve the two step approach through input parameter variation.