ABSTRACT
Automated guided vehicles are so crucial for transporting materials and products in manufacturing systems. AGVs' flexibility and cost-effectiveness are crucial for the manufacturing systems. This study aims to compare ant colony optimization (ACO) and genetic algorithm (GA) for routing AGVs. The implementation was developed using C# programming language. The AGVs' effectiveness has been increased. The study includes 12 nodes. The route of AGVs was determined, thanks to the developed application. As a result of this study, it can be said that ant colony algorithm can be more successful for solving traveling salesperson problems.
