Open AccessCOMPUTATIONAL GRIDS TO SOLVE LARGE SCALE OPTIMIZATION PROBLEMS WITH UNCERTAIN DATA
Author(s) -
Chefi Triki,
Lucio Grandinetti
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.1.1.78
Subject(s) - computer science , mathematical optimization , grid , scale (ratio) , path (computing) , optimization problem , stochastic optimization , algorithm , mathematics , physics , geometry , quantum mechanics , programming language
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 grid-enabled path-following algorithm and we discuss some experimental results.