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)
  • Received : 2012.11.04
  • Accepted : 2013.10.01
  • Published : 2013.10.25


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.


fiber-reinforced composite structure;generalized evolutionary optimization;discrete-type multi-objective optimization;genetic algorithm;artificial neural network


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