Title
A second-order cone programming approximation to joint chance-constrained linear programs
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.
Year
DOI
Venue
2012
10.1007/978-3-642-32147-4_8
ISCO
Keywords
Field
DocType
optimal value,stochastic linear program,random data,socps problem,stochastic program,joint chance-constrained linear program,probabilistic lot-sizing problem,latter stochastic program,random matrix,original problem,second-order cone programming approximation,approximated stochastic program
Second-order cone programming,Applied mathematics,Discrete mathematics,Upper and lower bounds,Probabilistic logic,Triangular matrix,Stochastic programming,Mathematics,Random matrix
Conference
Citations 
PageRank 
References 
3
0.48
10
Authors
3
Name
Order
Citations
PageRank
Jianqiang Cheng1729.66
Céline Gicquel283.28
Abdel Lisser316829.93