An improved version of the pruned-enriched-Rosenbluth method (PERM) is proposed and tested on finding lowest energy states in simple models of lattice heteropolymers. It is found to outperform not only the previous version of PERM, but also all other fully blind general purpose stochastic algorithms which have been employed on this problem. In many cases it found new lowest energy states missed in previous papers. Limitations are discussed.
@article{arxiv.cond-mat/0209366,
title = {A Growth-based Optimization Algorithm for Lattice Heteropolymers},
author = {Hsiao-Ping Hsu and Vishal Mehra and Walter Nadler and Peter Grassberger},
journal= {arXiv preprint arXiv:cond-mat/0209366},
year = {2009}
}