  In the paper a novel stochastic algorithm designed to study of chain-like
bodies dynamics is introduced. This algorithm models chain movements induced by
the tension propagation and its main idea relies on the sequentialization of
each movement into a sequence of virtual steps made by chain's segments. In
this spirit, any accepted chain's new position is achieved by a move that is
initiated by a shift of one segment picked randomly according to a
problem-specific probability distribution and then followed by a cascade of
some other segments' position rearrangements. The rearrangement process
terminates when the tension in the chain induced by the initial shift is
released. A considerable gain in the volume of allocated memory is achieved
because the virtual steps lead to new conformations that are very likely to be
acceptable by nature. We validate the algorithm by comparing passage times for
polymer translocation through a pore obtained within this algorithm with their
counterparts reported in the literature. In this paper we focus on a
fluctuating-bond model of self-avoiding polymers on 2D square lattice. Based on
the large data sets received in our simulations we have found that the
transolaction time is distributed according to the Moyal probability
distribution. This novel finding enables us to identify the theoretical form of
various distributions of translocation time reported in literature by
expressing them very accurately with the help of this two-parameter family of
probability distributions
