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Steel and Composite Structures
  Volume 15, Number 4, October 2013 , pages 451-466

Generalized evolutionary optimum design of fiber-reinforced tire belt structure
J.R. Cho, J.H. Lee, K.W. Kim and S.B. Lee

    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.
Key Words
    fiber-reinforced composite structure; generalized evolutionary optimization; discrete-type multi-objective optimization; genetic algorithm; artificial neural network
1) J.R. Cho, J.H. Lee and S.B. Lee: School of Mechanical Engineering, Pusan National University, Busan 609-735, Korea;
2) J.R. Cho: Research and Development Institute of Midas IT, Gyeonggi 463-400, Korea;
3) K.W. Kim: R&D Center of Kumho Tire Co. Ltd., Gwangju 500-757, Korea.

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