The Multi-Robot Task Allocation problem (MRTA) is the situation where we have a set of tasks and robots; then we must decide the assignments between robots and tasks in order to optimize a certain measure (e.g. allocate the maximum number of tasks...). We present an effective solution to resolve this problem by implementing a two-stage methodology: first a global allocation that uses the Firefly Algorithm (FA), next a local allocation that uses the set theory properties (Power Set algorithm). Finally, results of the different simulations show that our solution is efficient in terms of the rate of allocated tasks and the calculated allocations are locally optimal.