COMPARISON OF THE SUCCESS OF META-HEURISTIC ALGORITHMS IN TOOL PATH PLANNING OF COMPUTER NUMERICAL CONTROL MACHINE

作     者：Caska, Serkan Gok, Kadir Gok, Arif 

作者机构：Manisa Celal Bayar Univ Hasan Ferdi Turgutlu Technol Fac Dept Mech Engn TR-45300 Manisa Turkey Izmir Bakircay Univ Dept Biomed Engn Engn & Architecture Fac TR-35660 Izmir Turkey Kutahya Dumlupinar Univ Architecture Fac Dept Ind Design TR-43000 Kutahya Turkey 

出 版 物：《SURFACE REVIEW AND LETTERS》 (Surf. Rev. Lett.)

年 卷 期：2022年第29卷第9期

页      面：2250126-2250126页

核心收录：

学科分类：07[理学] 070203[理学-原子与分子物理] 0703[理学-化学] 0702[理学-物理学] 

主　　题：Computer numerical control machine genetic algorithms particle swarm optimization grey wolf optimizer travelling salesman problem 

摘      要：Carrying out an engineering process with the least cost and within the shortest time is the basic purpose in many fields of industry. In Computer Numerical Control (CNC) machining, performing a process by following a certain order reduces cost and time of the process. In the literature, there are research works involving varying methods that aim to minimize the length of the CNC machine tool path. In this study, the trajectory that the CNC machine tool follows while drilling holes on a plate was discussed within the Travelling Salesman Problem (TSP). Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO) methods were used to solve TSP. The case that the shortest tool path was obtained was determined by changing population size parameter in GA, PSO, and GWO methods. The results were presented in tables.