Computational grids to solve large scale optimization problems with uncertain data

Author

Triki, Chefi ; Grandinetti, Lucio

Author_Institution

Dept. of Electron., Inf. & Syst., Calabria Univ., Italy

fYear

2001

fDate

2001

Firstpage

124

Lastpage

127

Abstract

In this paper, we discuss the use of computational grids to solve stochastic optimization problems. These problems are generally difficult to solve and are often characterized by a high number of variables and constraints. Furthermore, for some applications, it is required to achieve a real-time solution. Obtaining reasonable results is a difficult objective without the use of high-performance computing. We present a grid-enabled path-following algorithm and we discuss some experimental results

Keywords

distributed programming; large-scale systems; mathematics computing; real-time systems; stochastic programming; uncertainty handling; 2-stage stochastic models; Condor; computational grids; constraints; grid-enabled path-following algorithm; high-performance computing; large-scale stochastic optimization problems; real-time solution; uncertain data; variables; Concurrent computing; Grid computing; Informatics; Iterative algorithms; Large-scale systems; Parallel algorithms; Random variables; Stochastic processes; Symmetric matrices; Uniform resource locators;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, International Workshop on, 2001.

Conference_Location

Crimea

Print_ISBN

0-7803-7164-X

Type

conf

DOI

10.1109/IDAACS.2001.941995

Filename

941995