Grid computing indeed is the next generation of distributed systems and its goals is creating a powerful virtual, great, and autonomous computer that is created using countless Heterogeneous resource with the purpose of sharing resources. Scheduling is one of the main steps to exploit the capabilities of emerging computing systems such as the grid. Scheduling of the jobs in computational grids due to Heterogeneous resources is known as an NP-Complete problem. Grid resources belong to different management domains and each applies different management policies. Since the nature of the grid is Heterogeneous and dynamic, techniques used in traditional systems cannot be applied to grid scheduling, therefore new methods must be found. This paper proposes a new algorithm which combines the firefly algorithm with the Max-Min algorithm for scheduling of jobs on the grid. The firefly algorithm is a new technique based on the swarm behavior that is inspired by social behavior of fireflies in nature. Fireflies move in the search space of problem to find the optimal or near-optimal solutions. Minimization of the makespan and flowtime of completing jobs simultaneously are the goals of this paper. Experiments and simulation results show that the proposed method has a better efficiency than other compared algorithms.