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

Autor:	SERKAN ÇAŞKA, KADIR GÖK, ARIF GÖK
Rok vydání:	2022
Předmět:	Materials Chemistry Surfaces and Interfaces Condensed Matter Physics Surfaces Coatings and Films
Zdroj:	Surface Review and Letters. 29
ISSN:	1793-6667 0218-625X
DOI:	10.1142/s0218625x22501268
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::13d1901f1e4744ad9a1c8d653eab4f66 https://doi.org/10.1142/s0218625x22501268 Zobrazit plný text záznamu