Optimization of Motion Trajectory in CNC Machines

This extensive analysis aims to identify all possible algorithms for solving traveling salesman problems and examines the models and optimization algorithms used in the control programs of postprocessors and process machines in the field of numerical interleaving (CNC). The study addresses geometric, kinematic and dynamic models, as well as process and optimization models, highlighting their roles in achieving efficient tool paths. CAD/CAM model integration, real-time adaptive control, and hybrid approaches are discussed to highlight their importance in the manufacturing process. Additionally, the abstract explores prominent optimization algorithms, including genetic algorithms, simulated annealing, ant colony optimization, particle swarm optimization, tabu list search, and differential evolution, explaining their applicability to solving challenges and achieving optimal solutions in tool path planning of numerically interleaved machine tools. (CNC).