Vehicle Routing Problems (VRP) represent a widely studied class of combinatorial optimization problems due to their applicability in various real-world contexts, particularly in commercial settings. The inherent complexity of VRP necessitates the use of computationally efficient approximation approaches, with metaheuristics emerging as prominent methods in this domain. This thesis aims to construct and develop several metaheuristic-based algorithms, primarily focusing on single-solution approaches, for addressing the Capacitated Vehicle Routing Problem (CVRP). Subsequently, these algorithms will be systematically compared against each other and against a state-of-the-art tools (Google Or-tools). Through this comparative study, insights into the efficacy and performance of different metaheuristic strategies in solving CVRP will be gained, contributing to the advancement of optimization methodologies in logistics and transportation management.