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In the paper a novel stochastic algorithm designed to study of chain-likebodies dynamics is introduced. This algorithm models chain movements induced bythe tension propagation and its main idea relies on the sequentialization ofeach movement into a sequence of virtual steps made by chain's segments. Inthis spirit, any accepted chain's new position is achieved by a move that isinitiated by a shift of one segment picked randomly according to aproblem-specific probability distribution and then followed by a cascade ofsome other segments' position rearrangements. The rearrangement processterminates when the tension in the chain induced by the initial shift isreleased. A considerable gain in the volume of allocated memory is achievedbecause the virtual steps lead to new conformations that are very likely to beacceptable by nature. We validate the algorithm by comparing passage times forpolymer translocation through a pore obtained within this algorithm with theircounterparts reported in the literature. In this paper we focus on afluctuating-bond model of self-avoiding polymers on 2D square lattice. Based onthe large data sets received in our simulations we have found that thetransolaction time is distributed according to the Moyal probabilitydistribution. This novel finding enables us to identify the theoretical form ofvarious distributions of translocation time reported in literature byexpressing them very accurately with the help of this two-parameter family ofprobability distributions

A sequential algorithm with a built in tension-propagation mechanism for modeling the chain-like bodies dynamics