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http://dx.doi.org/10.12989/scs.2013.15.4.451

Generalized evolutionary optimum design of fiber-reinforced tire belt structure  

Cho, J.R. (School of Mechanical Engineering, Pusan National University)
Lee, J.H. (School of Mechanical Engineering, Pusan National University)
Kim, K.W. (R&D Center of Kumho Tire Co. Ltd.)
Lee, S.B. (School of Mechanical Engineering, Pusan National University)
Publication Information
Steel and Composite Structures / v.15, no.4, 2013 , pp. 451-466 More about this Journal
Abstract
This paper deals with the multi-objective optimization of tire reinforcement structures such as the tread belt and the carcass path. The multi-objective functions are defined in terms of the discrete-type design variables and approximated by artificial neutral network, and the sensitivity analyses of these functions are replaced with the iterative genetic evolution. The multi-objective optimization algorithm introduced in this paper is not only highly CPU-time-efficient but it can also be applicable to other multi-objective optimization problems in which the objective function, the design variables and the constraints are not continuous but discrete. Through the illustrative numerical experiments, the fiber-reinforced tire belt structure is optimally tailored. The proposed multi-objective optimization algorithm is not limited to the tire reinforcement structure, but it can be applicable to the generalized multi-objective structural optimization problems in various engineering applications.
Keywords
fiber-reinforced composite structure; generalized evolutionary optimization; discrete-type multi-objective optimization; genetic algorithm; artificial neural network;
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Times Cited By KSCI : 2  (Citation Analysis)
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