DocumentCode
3140275
Title
The scenario approach to stochastic optimization
Author
Goodwin, Graham C. ; Cea, Mauricio G. ; Cooper, Hal J. ; Feuer, Arie
Author_Institution
Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Newcastle, NSW, Australia
fYear
2011
fDate
19-21 Dec. 2011
Firstpage
1
Lastpage
9
Abstract
Many design problems in control, telecommunications and signal processing can be expressed as optimization problems. Many of these problems are stochastic in the sense that they are parameterized by random/uncertain variables. The goal of the current paper is to review recent research on stochastic optimization. We specifically address the issue of scenario generation which lies at the heart of the solution to such problems.
Keywords
optimisation; stochastic processes; optimization problems; random variables; signal processing; stochastic optimization; telecommunications; uncertain variables; Approximation methods; Monte Carlo methods; Optimization; Probability distribution; Random variables; Stochastic processes; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation (ICCA), 2011 9th IEEE International Conference on
Conference_Location
Santiago
ISSN
1948-3449
Print_ISBN
978-1-4577-1475-7
Type
conf
DOI
10.1109/ICCA.2011.6138102
Filename
6138102
Link To Document