Optimization based on information containing uncertainties
Abstract
Considers the problem of finding extrema of an unknown function L(⋅):I Rl× R or the root set of its gradient f(⋅) \underline \underline Δ ▽ L(⋅) on the basis of observations, which may contain two kinds of uncertainties: random noise and structural uncertainties. The latter is caused by the fact that observations may not be made on the recent estimate, may not even be carried out on f(⋅) but on some other function. The optimization algorithm and conditions guaranteeing its convergence are given.
Keywords
Citation
Chen, H. (2001), "Optimization based on information containing uncertainties", Kybernetes, Vol. 30 No. 9/10, pp. 1177-1183. https://doi.org/10.1108/EUM0000000006548
Publisher
:MCB UP Ltd
Copyright © 2001, MCB UP Limited