Wireless Mesh Networks (WMNs) are an efficient solution for delivering reliable and extensive wireless services. These networks consist of interconnected mesh routers capable of dynamically routing data. Despite their advantages, WMNs face significant challenges during initial deployment, as determining the optimal placement of routers for effective coverage and connectivity is a complex process classified as NP-hard. This research introduces a hybrid simulation system that integrates Particle Swarm Optimization (PSO), Hill Climbing (HC), and Distributed Genetic Algorithm (DGA) to optimize router placement in WMNs. We consider Linearly Decreasing Vmax Method (LDVM) and Linearly Decreasing Inertia Weight Method (LDIWM) router replacement methods and compare Unimodal Normal Distribution Crossover (UNDX) and Simplex Crossover (SPX) crossover methods for two-islands mesh client distribution. The simulation results indicate that the combination of UNDX and LDIWM achieves superior load balancing, underscoring its potential for improving the efficiency of WMNs.