Çaşka S.Gök K.Gök A.2024-07-222024-07-2220220218625Xhttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/12546Carrying 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. © 2022 World Scientific Publishing Company.EnglishComputer control systemsCost engineeringHeuristic algorithmsMachine toolsMotion planningNumerical control systemsParticle swarm optimization (PSO)Population statisticsTraveling salesman problemComputer numerical control machinesGray wolf optimizerGray wolvesMeta-heuristics algorithmsNumerical control machine toolOptimizersParticle swarmParticle swarm optimizationSwarm optimizationToolpathsGenetic algorithmsArticle10.1142/S0218625X22501268