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The advent of Network Functions Virtualization (NFV) has revolutionized numerous network based applications due to its score of benefits such as flexibility, agility, scalability and Multi-tenancy. In this paper, we focus on the mapping of Virtual Network Function Forwarding Graphs (VNF-FGs) on a Substrate Network. To cope with this NP-Hard problem, we designed an algorithm based on Greedy Randomized Adaptive Search Procedure (GRASP), a cost-efficient meta-heuristic algorithm, in which the main objective is to minimize the mapping cost. Another method named MARA (Most Available Resource Algorithm) was devised with the objective of reducing the Substrate Network’s resources use at the bottleneck clusters. Performance analysis based on simulations are given to show the behavior and efficiency of our approaches.