Generalized Simulated Annealing
Condensed Matter
2015-06-25 v1
Abstract
We propose a new stochastic algorithm (generalized simulated annealing) for computationally finding the global minimum of a given (not necessarily convex) energy/cost function defined in a continuous D-dimensional space. This algorithm recovers, as particular cases, the so called classical ("Boltzmann machine") and fast ("Cauchy machine") simulated annealings, and can be quicker than both. Key-words: simulated annealing; nonconvex optimization; gradient descent; generalized statistical mechanics.
Cite
@article{arxiv.cond-mat/9501047,
title = {Generalized Simulated Annealing},
author = {Constantino Tsallis and Daniel A. Stariolo},
journal= {arXiv preprint arXiv:cond-mat/9501047},
year = {2015}
}
Comments
13 pages, latex, 4 figures available upon request with the authors.