Optimization of laser cutting path based on improved ant colony algorithm
                                                                        HOU Puliang, LIU Jianqun, GAO Weiqiang
                 (College of Mechanical and Electrical Engineering, Guangdong University of Technology, Guangzhou 510006, China)

Abstract: Aiming at the global path optimization of laser cutting processing, the traditional ant colony system algorithm has a slow convergence rate and easy to fall into local optimum, the improved ant colony system algorithm was studied. Using starting point and end point information of the laser processing entity, the mathematical model of the equivalent TSP problem of the entity was established. An improved algorithm for reoptimizing the path planning results of ant colony system algorithm by nearest neighbor insertion algorithm was proposed, the implementation steps of the improved ant colony system algorithm was described in detail, the iteration times and optimization results of the traditional ant colony system algorithm and the improved ant colony system algorithm were analyzed. The results indicate that the improved ant colony system algorithm accelerates the convergence speed, reduces the number of iterations by about 30%, shortens the total length of the path taken by the laser processing，and successfully applied to the selfdeveloped laser cutting processing system.

Key words: laser cutting;route planning; improved ant colony algorithm; nearest neighbor insertion algorithm