Due to the high propagation loss and blockage-sensitive characteristics of millimeter waves (mmWaves), constructing fifth-generation (5G) cellular networks involves deploying ultra-dense base stations (BSs) to achieve satisfactory communication service coverage. However, ultra-densely deployed BSs are associated with extremely high construction and operation costs for 5G cellular networks. Reducing the construction cost and decreasing the energy consumption of BSs under the premise of ensuring the quality and coverage of services have become major challenges for the rollout of 5G technology. Essentially, the location optimization of 5G BSs can be regarded as a type of maximum coverage location problem (MCLP). Hence, this study coupled geographic information system (GIS) and a heuristic optimization algorithm to spatially explicit simulate the propagation of 5G signals and to optimize the service coverage of 5G BSs. The developed model was applied to search for the optimal solutions in 5G cellular network planning for an urban outdoor area in Wuhan, China. The optimal solutions and comparative experiments demonstrate that the proposed model can provide reasonable and robust results to support 5G cellular network planning. Therefore, this approach can help address the cost and energy consumption challenges faced in constructing 5G infrastructures and facilitate the rollout of 5G technology.