Wireless Mesh Networks (WMNs) are an important networking infrastructure for providing cost-efficient broadband wireless connectivity to a group of users. WMNs are increasingly being used in urban, metropolitan and municipal area networks for deployment of medical, transport, surveillance systems, etc. The performance and operability of WMNs largely depends on placement of mesh routers nodes in the geographical area to achieve network connectivity and stability. The objective is to find an optimal and robust topology of the mesh router network to support intelligent telecommunication services to clients such as adaptive and flexible wireless Internet access, mobile data, voice, video in addition to supporting other preferred client services. In this work, we propose and evaluate local search methods for intelligent placement of mesh routers in WMNs with a two fold objective: maximizing the size of the giant component in the network and user coverage. Given a grid area where to distribute a given number of mesh router nodes, which can have different radio coverage, and a number of fixed clients a priori distributed in the given area, local search methods explore different local movements and incrementally improve the quality of the router nodes placement in terms of network connectivity and user coverage. We have experimentally evaluated the proposed local search methods through a benchmark of generated instances of varying sizes. Moreover, different distributions of mesh clients (Uniform, Normal, Exponential and Weibull) are used. The experimental evaluation showed the good performance of local search methods for optimizing network connectivity and user coverage in WMNs.