COMPARISON OF THE SUCCESS OF META-HEURISTIC ALGORITHMS IN TOOL PATH PLANNING OF COMPUTER NUMERICAL CONTROL MACHINE
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Date
2022
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Abstract
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. © 2022 World Scientific Publishing Company.
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Computer control systems , Cost engineering , Heuristic algorithms , Machine tools , Motion planning , Numerical control systems , Particle swarm optimization (PSO) , Population statistics , Traveling salesman problem , Computer numerical control machines , Gray wolf optimizer , Gray wolves , Meta-heuristics algorithms , Numerical control machine tool , Optimizers , Particle swarm , Particle swarm optimization , Swarm optimization , Toolpaths , Genetic algorithms