| Article ID: | iaor20102909 |
| Volume: | 36 |
| Issue: | 6 |
| Start Page Number: | 665 |
| End Page Number: | 668 |
| Publication Date: | Nov 2008 |
| Journal: | Operations Research Letters |
| Authors: | Smith Robert L, Ghate Archis |
| Keywords: | programming: dynamic |
Markov chain methods for Boltzmann sampling work in phases with decreasing temperatures. The number of transitions in each phase crucially affects terminal state distribution. We employ dynamic programming to allocate iterations to phases to improve guarantees on sample quality. Numerical experiments on the Ising model are presented.