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: Technology and Applications, IDAACS 2001
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages124-127
Number of pages4
ISBN (Print)078037164X, 9780780371644
DOIs
Publication statusPublished - 2001
EventInternational Workshop on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2001 - Foros, Crimea, Ukraine
Duration: Jul 1 2001Jul 4 2001

Other

OtherInternational Workshop on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2001
CountryUkraine
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

Cite this

Triki, C., & Grandinetti, L. (2001). Computational grids to solve large scale optimization problems with uncertain data. In Proceedings of the International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2001 (pp. 124-127). [941995] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IDAACS.2001.941995