In this paper, a general Combinatorial Ant System-based distributed routing algorithm modeled like a dynamic combinatorial optimization problem is presented. In the proposed algorithm, the solution space of the dynamic combinatorial optimization problem is mapped into the space where the ants will walk, and the transition probability and the pheromone update formula of the Ant System is defined according to the objective function of the communication problem. The general nature of the approach allows for the optimization of the routing function to be applied in different types of networks just changing the performance criteria to be optimized. In fact, we test and compare the performance of our routing algorithm against well-known routing schemes for wired and wireless networks, and show its superior performance in terms throughput, delay and energy efficiency.