In this paper, we try to solve the problem of ‘Maximum Network Coverage’ for University of Minnesota wireless network domain. We propose a mathematical model, based on tree-based evolutionary genetic algorithms, that takes the dimension of a building (in UMN campus) as input and finds the optimal number of wireless access points and their corresponding positions. Placing too few access points results in coverage gaps and too many increases the deployment cost. The proposed method iterates over all the parameters and converges to an optimum solution for number and position of access points. The results obtained for the Ford Hall building indicate that we obtained the same network coverage as the current wireless access point deployment, but, with lesser number of access points.