Some Remarks on the Optimal Level of Randomization in Global Optimization
Optimization and Control
2025-10-20 v1 Numerical Analysis
Numerical Analysis
Probability
Abstract
For a class of stochastic restart algorithms we address the effect of a nonzero level of randomization in maximizing the convergence rate for general energy landscapes. The resulting characterization of the optimal level of randomization is investigated computationally for random as well as parametric families of rugged energy landscapes.
Keywords
Cite
@article{arxiv.math/0406095,
title = {Some Remarks on the Optimal Level of Randomization in Global Optimization},
author = {Ted Theodosopoulos},
journal= {arXiv preprint arXiv:math/0406095},
year = {2025}
}
Comments
16 pages, 8 figures, presented at the DIMACS Workshop on Randomization Methods in Algorithm Design, 1997