Modern telecommunications are supporting every day a progressive demand for services, which in turn generates greater requirements from the attention capacity in photonic transport networks. This phenomenon forces us to improve the routing systems, to minimize the blocking probability and minimize the use of the network, among other indicators, in order to attend current demand and to have the capacity to attend future demand. This paper compares four studies on routing and wavelength assignment with the aim of supporting the improvement of the already mentioned indicators. A comparison is made between optimizing algorithms and heuristic simulated annealing and genetic algorithms, using comparative indicators such as blocking probability and the use of the network. The results show that the heuristic algorithms are potentially better for a high load dynamic demand (greater than 120 erlangs) that would function much better under stress. GINT proposes genetic algorithms as a solution to the coming future demand of data transport.