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ABSTRACT

Numerical prediction and sequential process optimization in sheet forming based on genetic algorithm

Schmidt1

Corresponding author. Department of Mechanical Engineering, Lipetsk State Technical University, Lipetsk, Russia. Tel.: +1 (773) 293-3115; fax: +1 (773) 213-9907. E-mail address:me@alexschmidt.net (A. Schmidt).

The International Conference on Computational & Experimental Engineering and Sciences 2010, 15(2), 65-74. https://doi.org/10.3970/icces.2010.015.065

Abstract

Genetic algorithm is an emerging technique used in engineering design activities to find an optimized solution which satisfy a number of design goals. Non-linear direct method of goal search use successive linearization techniques, which are sensitive to the chosen starting solution and quality of the objective function. The proposed technique can solve programming problems having non-convex regions, which are usually avoided in classical optimization problems. The efficacy of the proposed novel method is demonstrated by solving a number of test problems. The results suggest that the proposed method is effective and represents a practical tool for solving sheet forming problems.

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Cite This Article

APA Style
Schmidt, (2010). Numerical prediction and sequential process optimization in sheet forming based on genetic algorithm. The International Conference on Computational & Experimental Engineering and Sciences, 15(2), 65-74. https://doi.org/10.3970/icces.2010.015.065
Vancouver Style
Schmidt . Numerical prediction and sequential process optimization in sheet forming based on genetic algorithm. Int Conf Comput Exp Eng Sciences . 2010;15(2):65-74 https://doi.org/10.3970/icces.2010.015.065
IEEE Style
Schmidt, “Numerical prediction and sequential process optimization in sheet forming based on genetic algorithm,” Int. Conf. Comput. Exp. Eng. Sciences , vol. 15, no. 2, pp. 65-74, 2010. https://doi.org/10.3970/icces.2010.015.065



cc Copyright © 2010 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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