Computational grids to solve large scale optimization problems with uncertain data

Chefi Triki, Lucio Grandinetti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper we discuss the use 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. Here we present a gridenabled path-following algorithm and we discuss some experimental results.

Original languageEnglish
Title of host publicationProceedings of the International Workshop on Intelligent Data Acquisition and Advanced Computing Systems
Subtitle of host publicationTechnology and Applications, IDAACS 2001
EditorsAnatoly Sachenko
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages124-127
Number of pages4
ISBN (Electronic)078037164X, 9780780371644
DOIs
Publication statusPublished - 2001
Externally publishedYes
EventInternational Workshop on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2001 - Foros, Crimea, Ukraine
Duration: Jul 1 2001Jul 4 2001

Publication series

NameProceedings of the International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2001

Other

OtherInternational Workshop on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2001
Country/TerritoryUkraine
CityForos, Crimea
Period7/1/017/4/01

Keywords

  • Condor
  • Grid computation
  • Large-scale optimization problems
  • Two stage stochastic models

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing
  • Computer Science (miscellaneous)
  • Computer Science Applications

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