Optimization Algorithms Based on Renormalization Group
Disordered Systems and Neural Networks
2009-10-31 v2
Abstract
Global changes of states are of crucial importance in optimization algorithms. We review some heuristic algorithms in which global updates are realized by a sort of real-space renormalization group transformation. Emphasis is on the relationship between the structure of low-energy excitations and ``block-spins'' appearing in the algorithms. We also discuss the implication of existence of a finite-temperature phase transition on the computational complexity of the ground-state problem.
Cite
@article{arxiv.cond-mat/9911142,
title = {Optimization Algorithms Based on Renormalization Group},
author = {Naoki Kawashima},
journal= {arXiv preprint arXiv:cond-mat/9911142},
year = {2009}
}
Comments
7 pages, 2 figures