Finding the maximum independent set (MaxIS) of a general graph is an NP-hard problem. In this paper, we propose a hybrid algorithm combining Grey Wolf Optimizer (GWO) and Genetic Algorithm (GA) to find the Maximum Independent Set in a graph. The algorithm leverages the exploration capabilities of GWO and the exploitation strengths of GA to efficiently explore the search space and find high-quality solutions. The experimental results demonstrate the effectiveness of the proposed hybrid algorithm. We also compare the GWO_GA algorithm and its performance with GWO, GA, GA_GWO algorithms. The result shows that our proposed algorithm performs better than other discussed algorithms.