As one innovative paradigm, reconfigurable intelligent surface (RIS) has been applied to enhance coverage in wireless communication networks by providing a virtual connection between the transmitter and the receiver in scenarios where line-of-sight (LoS) is obstructed. In this work, the issue of optimizing multi-RIS deployment locations is considered to enhance coverage while reducing network costs. We first develop a method based on approximate cell decomposition to quantitatively calculate the coverage probability in RIS-assisted outdoor wireless communication networks. Then we propose a RIS location optimization strategy, Rule-based and Brand-and-Bound-based (B&B), called R&B algorithm to strike a balance between coverage probability and network cost. The Rule-based algorithm is applied to obtain feasible solutions, and the B&B algorithm is proposed to optimize the RISs deployment locations to enhance coverage probability while satisfying network cost constraints. Numerical results show that the proposed method outperforms the other baseline schemes to trade off coverage probability and network cost in a multi-obstacle wireless communication environment with sufficient RIS.