| Journal: | Journal of applied research and technology |
| Database: | PERIÓDICA |
| System number: | 000370566 |
| ISSN: | 1665-6423 |
| Authors: | Belloufi, A1 Assas, M2 Rezgui, I3 |
| Institutions: | 1Universite Mohamed Khider, Department of Mechanical Engineering, Biskra. Argelia 2University Hadj Lakhder, Department of Mechanical Engineering, Batna Batna. Argelia 3Universite Kasdi Merbah Ouargla, Ouargla Ouargla. Argelia |
| Year: | 2013 |
| Season: | Feb |
| Volumen: | 11 |
| Number: | 1 |
| Country: | México |
| Language: | Inglés |
| Document type: | Artículo |
| Approach: | Experimental, aplicado |
| English abstract | The determination of optimal cutting parameters is one of the most important elements in any process planning of metal parts. In this paper, a new hybrid genetic algorithm by using sequential quadratic programming is used for the optimization of cutting conditions. It is used for the resolution of a multipass turning optimization case by minimizing the production cost under a set of machining constraints. The genetic algorithm (GA) is the main optimizer of this algorithm whereas SQP Is used to fine tune the results obtained from the GA. Furthermore, the convergence characteristics and robustness of the proposed method have been explored through comparisons with results reported in literature. The obtained results indicate that the proposed hybrid genetic algorithm by using a sequential quadratic programming is effective compared to other techniques carried out by different researchers |
| Disciplines: | Ingeniería |
| Keyword: | Ingeniería mecánica, Programación cuadrática secuencial, Condiciones de corte, Algoritmos |
| Keyword: | Engineering, Mechanical engineering, Sequential quadratic programming, Cutting conditions, Algorithms |
| Full text: | Texto completo (Ver HTML) |
