Biased Monte Carlo methods
Polymer simulations make extensive use of biased Monte Carlo schemes. In this paper, I describe a subset of polymer-simulation algorithms that aim to increase the sampling effeciency by biasing the selection of trial moves. Algorithms that belong to this category are the Configurarional Bias MC method (CBMC), Dynamical Pruned Enriched Rosenbluth sampling (DPERM) and Recoil-Growth (RG) sampling.