Multicast services are increased in exponential manner in these last few years and in particular in the field of multimedia services. Multicast can reduce resources allocation and enhance network performances in terms of QoS, especially in a wireless platforms where the bandwidth is a precious resource. The problem of multicast routing can be reduced to the problem of finding a spanning tree capable to distribute network flow among multicast sources and destinations. It has been established that determining an optimal multicast tree for a static multicast group can be modeled as the Steiner Tree problem in networking, this problem has been proofed to be a NP-complete. Hence the necessity of using scalable algorithms in scalable networks composed of multi layered platforms. Moreover, in this work a QoS multi-constraint multicast problem has been addressed. In this paper a comparison between two meta-heuristic algorithms is presented in order to show the scalability introduced by these types of algorithms that are able of finding sub-optimal solutions. These meta-heuristics are based on Genetic Algorithm and Simulated Annealing mechanism. A simulated campaigns between two proposed algorithm has been addressed.