Optimal budget allocation in the evaluation of simulation-optimization algorithms. Guo, E. A. & Henderson, S. G. 2013. Unpublished Manuscript![Optimal budget allocation in the evaluation of simulation-optimization algorithms [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper abstract bibtex 1 download To efficiently evaluate simulation-optimization algorithms, we propose three different performance measures and their respective estimators. Only one estimator achieves the canonical Monte Carlo convergence rate $O(T^{−1/2})$, while the other two converge at the sub-canonical rate of $O(T^{−1/3})$. For each estimator, we study how the computational budget should be allocated between the execution of the optimization algorithm and the assessment of the output, so that the mean squared error of the estimator is minimized.
@unpublished{guohen11,
abstract = {To efficiently evaluate simulation-optimization algorithms, we propose three different performance measures and their respective estimators. Only one estimator achieves the canonical Monte Carlo convergence rate $O(T^{−1/2})$, while the other two converge at the sub-canonical rate of $O(T^{−1/3})$. For each estimator, we study how the computational budget should be allocated between the execution of the optimization algorithm and the assessment of the output, so that the mean squared error of the estimator is minimized.},
author = {Eric Anjie Guo and Shane G. Henderson},
date-added = {2016-01-10 16:07:54 +0000},
date-modified = {2016-01-10 16:07:54 +0000},
note = {Unpublished Manuscript},
title = {Optimal budget allocation in the evaluation of simulation-optimization algorithms},
url_paper = {pubs/guohen13.pdf},
year = {2013}}