Genetik algoritmalar ve mekanik tasarım problemleri uygulamaları

Bu çalısmada Yapay Zeka (YZ) tekniklerinden bir tanesi olan Genetik Algoritmalar’ın (GA), mekanik tasarım problemlerine uygulanma yöntemleri incelenmistir. GA’lar biyolojik sistemlerin gelisim sürecini simüle eden bir stokastik arama yöntemidir. Arastırılan çalısmalarda GA’nın mekanik tasarım problemlerine uygulanmasında ki amaçlar, bu amaçları sağlayacak matematiksel modeller ve bu modellerde kullanılan tasarım değiskenleri incelenmistir. Yapılan çalısmalardaki farklılıklar ve benzerlikler incelenmistir. Bunların mekanik tasarım problemlerinde sağladığı avantaj ve dezavantajlar belirlenmeye çalısılmıstır. Mekanik tasarım problemlerinin analitik veya sayısal analiz çözümlerinin yanında GA ile yapılan çözümlerinde uygun veriler elde edildiği görülmüs ve global optimizasyon da GA’nın daha basarılı çözümler bulduğu saptanmıstır.

Genetic algorithms and their application to mechanical design problems

In this study, application methods of Genetic Algorithms (GA) one of Artificial Intelligence (AI) techniques to mechanical design problems were examined. GA, which simulates the development of biological systems, is stochastic searching method. In the reviewed studies, purposes for application of GA to mechanical design problems, mathematical models fulfilling these purposes and design variations in these models were examined. The advantages and disadvantages ere tried to be determined. The similarities and differences in the performed studies were examined. The advantages and disadvantages of these in mechanical design problems were tried to be determined. It was seen that solutions of mechanical design problems through GA produced suitable data in addition to their analytical and numerical solutions and GA was found to produce more successful results in global optimisation.

PDF

___

1. Gülesin, M., “Process Planning in Design and Manufacturing Systems, Expert Systems, Edited by Cornalius T. Leondes, Vol. 2, Academic Press,. (2002)
2. Holland, J. H., “Adaptation in Natural and Artificial Systems”, University of Michigan Press, Ann Arbor, (1975).
3. Chambers, L., “Practical Handbook of Genetic Algorithms, Crc Press, 30-95 (1995).
4. Goldberg, D. E., “Genetic Algorithms in Search, Optimization and Machine Learning”, Addison Wesley, New York, (1989).
5. Altıparmak F., “Genetik Algoritmalar”, Gazi Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 11 (3): 523-541 (1998).
6. Srinivas M and Patnaik LM. “Genetic Algorithms: A survey”, IEEE Computer, 17-26, June (1994).
7. Gen, M., Cheng, R., “Genetic Algorithms and Engineering Design”, John Wiley & Sons Inc., New York 10-50 (1997).
8. Genetic Algorithms. “www.doc.ic.ac.uk/~nd/surprise_96/journal/vol1/tcw2/article1.html”. (07/05/2002).
9. Gen M. ve Cheng R., “Genetic Algorithms and Engineering Optimization", John Wiley&Sons, Inc., USA., (2000).
10. Pomrehn, L. P., Papalamb ros, P. Y., “Discrete Optimal Formulation with Application to Gear Train Design “, ASME J. of Mech. Design, 117(3): 419-424 (1995).
11. Ognjanovic, M., “Decisions in gear train transmission design”, Research in Engineering Design, 8(3): 178-187 (1996).
12. Flodin, A., “Wear investigation of spur gear teeth”, TriboTest, 7 (1): 45-60 (2000).
13. Dolen, M., Kaplan, H., Seireg, A., “Discrete Parameter-Nonlinear Constrained Optimization of a Gear Train Using Genetic Algorithms”, International Journal of Computer Applications in Technology, 24: 110-121 (2005).
14. Su, D., Wakelam, M., Jambunathan, K., “Integration Of A Knowledge-Based System, Artificial Neural Networks And Multimedia for Gear Design”, Journal of Materials Processing Technology, 107 (1-3): 53-59 (2000).
15. Chen, M., “Expert system of designing cylindric gear transmission”, Journal of Nanjing University of Science and Technology, 22 (5): 402-406 (1998).
16. Liansheng, Z.R., 1992, “Expert system for cylindrical gear reducer design”, Journal of Xi'an Jiaotong University, 26 (2): 29-38 (1992).
17. Myint, S., Tabucanon, M. T., “The framework for an expert system to generate alternative products in concurrent engineering design”, Computers in Industry, 37 (2): 125-134 (1998).
18. Abersek, B., Popov, V., “Intelligent tutoring system for training in design and manufacturing”, Advances in Engineering Software, 35: 461–471 (2004).
19. Marcelin, J. L., “Genetic optimization of gear”, International Journal of Advanced Manufacturing Technology, 17: 910-915 (2001).
20. Yokota, T., Taguchi, T. and Gen, M., “A solution method for optimal weight design problem of the gear using genetic algorithms”, Computers and Industrial Engineering, 35 (3-4): 523-526 (1998).
21. Li, Q., Zhou, J., Zhong, Y., “Complex genetic algorithm for mechanical dynamic optimization design”, Chinese Journal of Mechanical Engineering, 35 (5): 27-30 (1999).
22. Duan, G., Zha, J., Lin, J., and Weng, Q., “Use of genetic algorithms in designing movements of clocks and watches”, Journal of Software, 9 (7): 515-519 (1998).
23. Myint, S., “Concurrent engineering (CE) in product design: a multicriteria decision-making approach”, Concurrent Engineering Research and Applications, 7 (1): 2-9 (1999).
24. Tan, J., Fan, W., Wei, X., Xu, J., “Approach to graphic genetic modelon”, Journal of Computer Science and Technology, 13: 116-123 (1998).
25. Shariat, P.M., and Toogood, R.W., “Genetic algorithm based approach to parametric design of machine components”, Intelligent Engineering Systems Through Artificial Neural Networks, ASME, 5: 375-380 (1995).
26. Peng, Z., Yang, H., and Zhong, T., “Real-coded genetic algorithm for planetary gear transmission optimization”, Journal of Shanghai Jiaotong University, 33 (7): 833-836 (1999).
27. Fan, X., Ma, D., Yan, J., and Chen, M., “Hierarchical optimization for geometrical dimension tolerances”, Journal of Shanghai Jiaotong University, 33 (7): 829-832 (1999).
28. Gaspersic, J., Flasker, J., “Optimisation of gear assemblies”, Journal of Mechanical Engineering, 42 (9-10): 299-308 (1996).
29. Liu, P., Hu, Y., Yan, Y., Zheng, D., Yang, S., “Using counter-proposal to optimize genetic algorithm based cooperative negotiation”, Proceedings of the IEEE International Conference on Intelligent Processing Systems, ICIPS, 1: 891-895 (1998).
30. Deb, K., Goyal, M., “A flexible optimization procedure for mechanical component design based on genetic adaptive search”, Journal of Mechanical Design Transactions of the ASME, 120: 162-164 (1998).
31. Noorul H. A., Sivakumar, K.,· Saravanan, R.,· Muthiah, V., “Tolerance design optimization of machine elements using genetic algorithm”, International Journal of Advanced Manufacturing Technology, 25: 385– 391 (2005).
32. Deb, K., Jain, S., “Multi speed gearbox design using multi objective evolutionary algorithms”, KanGAL Report No. 2002001
33. Rao, A.C., “A genetic algorithm for epicyclic gear trains”, Mechanism and Machine Theory, 38: 135–147 (2003).
34. Samanta B., “Gear fault detection using artificial neural networks and support vector machines with genetic algorithms”, Mechanical Systems and Signal Processing, 18: 625–644 (2004).
35. Samanta, B., “Artificial neural networks and genetic algorithms for gear fault detection”, Mechanical Systems and Signal Processing, 18: 1273-1282, (2004).
36. Caligiana, G., Saggiani G. M., Bombardi, T., “ Application of fuzzy-genetic algorithms to mechanical optimizaton”, Atti del XI ADM International Conference, Palermo, sessione A, 95-104 (1999).
37. Zeyveli, M., Göloğlu, C., Dündar, K., “Düz Disli Hız Kutusunun Genetik Algoritma Đle Eniyilenmesi ” , 4th International Advanced Technologies Symposium, September 28–30, Konya / Türkiye, (2005).
38. Saruhan, H., and Rouch, K. E., “Optimization of Lubricant Film Thickness in Journal Bearings Using Genetic Algorithms”, Balkantrib Sempozyomu, Kayseri, 367-374 (2002).
39. Chakraborty, I., Kumara, V., Nair S. B., Tiwari, R., “Rolling element bearing design through genetic algorithms”, Engineering Optimization, 35 (6): 649–659 (2003).
40. Gupta, S., Tiwari, R., Nair, S. B., “Multi-objective design optimization of rolling bearings using genetic algorithms”, Mechanism and Machine Theory, doi:10.1016/j.mechmachtheory.2006.10.002
41. Rao, B. R., Tiwari, R., “Optimum design of rolling element bearings using genetic algorithms”, Mechanism and Machine Theory, 42: 233–250 (2007).
42. Mundo, D., Yan H. S., “Kinematic optimization of ball-screw transmission mechanisms”, Mechanism and Machine Theory, 42: 34–47 (2007).
43. Griffiths, D.R., Miles, J.C., “Determining the optimal cross-section of beams”, Advanced Engineering Informatics, 17: 59–76 (2003).
44. Kunjur A., Krishnamurty S., “Genetic algorithms in mechanismsynthesis”, Fourth Applied Mechanisms and Robotics Conference, (1995).
45. Roston G.D., Sturges R. H., “Genetic algorithm synthesis of four-bar mechanisms”, Artif. Intel. Engng. Des, Anal Manufact., 10: 371–90 (1996).

Makine Teknolojileri Elektronik Dergisi (elektronik)-Cover

ISSN: 1304-4141
Yayın Aralığı: Yılda 5 Sayı
Başlangıç: 2004
Yayıncı: -

Arşiv