It is very complicated to study the three-dimensional deformation of metal during rolling. The conventional finite element numerical analysis method generally adopts a fixed algorithm to calculate the whole rolling process. This method consumes huge computing power and sacrifices some computing accuracy. In this paper, according to the characteristics of different rolling stages, on the basis of considering the degree of metal deformation, a particle swarm hybrid algorithm with adaptive weight-learning factor is proposed.The Zoutendijk algorithm, Rosen algorithm, Wolfe algorithm and particle swarm hybrid algorithm are used to numerically simulate the rolling transverse thickness distribution. The accuracy of the rolling model and the particle swarm hybrid algorithm are verified. The influence of work roll edge contact and asymmetric roll bending on the deformation of rolling metal is analysed based on particle swarm mixing algorithm.
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