DocumentCode
3196118
Title
Newton´s method for optimization with probabilistic estimation
Author
Lockman, D. ; Mukai, H.
Author_Institution
Dept. of Syst. Sci. & Math., Washington Univ., St. Louis, MO, USA
Volume
4
fYear
1996
fDate
11-13 Dec 1996
Firstpage
3825
Abstract
Optimization problems are sometimes characterized by an objective function that cannot be directly evaluated but must be estimated, for example by sampling or Monte Carlo simulation. We propose a stabilized Newton´s method aimed at solving a certain class of such problems. Convergence of the proposed algorithm to stationary points is shown, under suitable assumptions
Keywords
Newton method; convergence of numerical methods; estimation theory; optimisation; probability; convergence; objective function; probabilistic estimation; stabilized Newton method; stochastic optimization; Convergence; Costs; H infinity control; Newton method; Optimal control; Optimization methods; Sampling methods; Stochastic processes; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1996., Proceedings of the 35th IEEE Conference on
Conference_Location
Kobe
ISSN
0191-2216
Print_ISBN
0-7803-3590-2
Type
conf
DOI
10.1109/CDC.1996.577248
Filename
577248
Link To Document