A second-order cone programming approximation to joint chance-constrained linear programs

Jianqiang Cheng, Céline Gicquel, Abdel Lisser

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

7 Scopus citations

Abstract

We study stochastic linear programs with joint chance constraints, where the random matrix is a special triangular matrix and the random data are assumed to be normally distributed. The problem can be approximated by another stochastic program, whose optimal value is an upper bound of the original problem. The latter stochastic program can be approximated by two second-order cone programming (SOCP) problems [5]. Furthermore, in some cases, the optimal values of the two SOCPs problems provide a lower bound and an upper bound of the approximated stochastic program respectively. Finally, numerical examples with probabilistic lot-sizing problems are given to illustrate the effectiveness of the two approximations.

Original languageEnglish (US)
Title of host publicationCombinatorial Optimization - Second International Symposium, ISCO 2012, Revised Selected Papers
Pages71-80
Number of pages10
DOIs
StatePublished - 2012
Externally publishedYes
Event2nd International Symposium on Combinatorial Optimization, ISCO 2012 - Athens, Greece
Duration: Apr 19 2012Apr 21 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7422 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Symposium on Combinatorial Optimization, ISCO 2012
Country/TerritoryGreece
CityAthens
Period4/19/124/21/12

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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