TY - JOUR
ID - 14429
TI - A homogeneous predictor-corrector algorithm for stochastic nonsymmetric convex conic optimization with discrete support
JO - Communications in Combinatorics and Optimization
JA - CCO
LA - en
SN - 2538-2128
AU - Alzalg, Baha
AU - Alabedalhadi, Mohammad
AD - Department of Mathematics,
The University of Jordan.
AD - Math Dept, Balqa Applied University
Y1 - 2023
PY - 2023
VL - 8
IS - 3
SP - 531
EP - 559
KW - Convex optimization
KW - Nonsymmetric programming
KW - Stochastic programming
KW - predictor-corrector methods
KW - Interior-point methods
DO - 10.22049/cco.2022.27449.1266
N2 - We consider a stochastic convex optimization problem over nonsymmetric cones with discrete support. This class of optimization problems has not been studied yet. By using a logarithmically homogeneous self-concordant barrier function, we present a homogeneous predictor-corrector interior-point algorithm for solving stochastic nonsymmetric conic optimization problems. We also derive an iteration bound for the proposed algorithm. Our main result is that we uniquely combine a nonsymmetric algorithm with efficient methods for computing the predictor and corrector directions. Finally, we describe a realistic application and present computational results for instances of the stochastic facility location problem formulated as a stochastic nonsymmetric convex conic optimization problem.
UR - http://comb-opt.azaruniv.ac.ir/article_14429.html
L1 - http://comb-opt.azaruniv.ac.ir/article_14429_0fbdc3396bab022b9b1e59d06fe7b586.pdf
ER -