Cutting parameters optimization and constraints investigation for turning process by GA with self-organizing adaptive penalty strategy

JSME International Journal, Series C: Mechanical Systems, Machine Elements and Manufacturing

Volumn 49, Issue 2, 2006, Pages 293-300

  Ahmad, Nafis ^a   Tanaka, Tomohisa ^a   Saito, Yoshio ^a  

^a TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

Cutting parameters; GA; Optimization; SOAP; Turning

Indexed keywords

CONSTRAINT THEORY; CUTTING; GENETIC ALGORITHMS; MACHINE TOOLS; OPTIMIZATION;

CUTTING PARAMETERS; SELF ORGANIZING ADAPTIVE PENALTY; TOOL-CHIP INTERFACE TEMPERATURE;

TURNING;

CONSTRAINT THEORY; CUTTING; GENETIC ALGORITHMS; MACHINE TOOLS; OPTIMIZATION; TURNING;

EID: 33845646919     PISSN: 13447653     EISSN: 1347538X     Source Type: Journal    
DOI: 10.1299/jsmec.49.293     Document Type: Article

References (12)

1. Ahmad, N., Tanaka, T. and Saito, Y., Investigation of Constraints for Optimization of Turning Process by GA with Self-Organizing Penalty Strategy, Proc. of the 3rd International Conference on Leading Edge Manufacturing in 21st Century, Nagoya, Japan, Vol.2 (2005), pp.319-324.
2. Ahmad, N., Tanaka, T. and Saito, Y., Optimization of Turning Process Parameters by Genetic Algorithm (GA) Considering the Effect of Tool Wear, Proc. of the 5th Manuf. and Machine Tool Conf. of JSME, Osaka, Japan, No.04-3, (2004), pp.305-306.
3. Lin, C.-Y. and Wu, W.-H., Self-Organizing Adaptive Penalty Strategy in Constrained Genetic Search, Struct Multidisc. Optim., Vol.26, No.6 (2004), pp.417-428.
4. Amiolemhen, P.E and Ibhadode, A.O.A., Application of Genetic Algorithms - Determination of the Optimal Machining Parameters in the Conversion of a Cylindrical Bar Stock into a Continuous Finished Profile, Int. J. of Machine Tools and Manuf., Vol.44, No.12-13 (2004), pp.1403-1412.
5. Saravanan, R., Asokan, P. and Vijayakumar, K., Machining Parameters Optimization for Turning Cylindrical Stock into a Continuous Finished Profile Using Genetic Algorithm (GA) and Simulated Annealing (SA), Int. J. Adv. Manuf. Technology, Vol.21, No.1 (2003), pp.1-9.
6. Vijayakumar, K., Prabhaharan, G., Asokan, P. and Saravanan, R., Optimization of Multi-Pass Turning Operations Using Ant Colony System, Int. J. of Machine Tools and Manuf., Vol.43 (2003), pp.1633-1639.
7. Onwubolu, G.C. and Kumalo, T., Optimization of Multipass Turning Operations with Genetic Algorithms, Int. J. Prod. Res., Vol.39, No.16 (2001), pp.3727-3745.
8. Meng, Q., Arsecularatne, J.A. and Mathew, P., Calculation of Optimum Cutting Conditions for Turning Operations Using a Machining Theory, Int. J. Machine Tool and Manuf., Vol.40, No.12 (2000), pp.1709-1733.
9. Goldberg, D.E., Genetic Algorithm in Search, Optimization & Machine Learning, 3rd Indian Edition, (2000), Addison Wesley.
10. Reddy, B.S.V., Shunmugam, M.S. and Narendran, T.T., Optimal Sub-Division of the Depth of Cut to Achieve Minimum, Production Cost in Multi-Pass Turning Using a Genetic Algorithm, J. of Mat. Proc. Tech., Vol.79, No.1-3 (1998), pp.101-108.
11. Kee, P.K., Development of Constrained Optimization Analyses and Strategies for Multi-Pass Rough Turning Operations, Int. J. Mach. Tools Manuf., Vol.36, No.1 (1996), pp.115-127.
12. Chris, H., Jeff, J. and Mike, K., A Genetic Algorithm for Function Optimization: A Matlab Implementation, NCSU-IE TR 95-09, (1995).