A path-following algorithm for stochastic quadratically constrained convex quadratic programming in a Hilbert space

Author(s):

Amira Achouak Oulha , Baha Alzalg *

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
We propose logarithmic-barrier decomposition-based interior-point algorithms for solving two-stage stochastic quadratically constrained convex quadratic programming problems in a Hilbert space. We prove the polynomial complexity of the proposed algorithms, and show that this complexity is independent on the choice of the Hilbert space, and hence it coincides with the best-known complexity estimates in the finite-dimensional case. We also apply our results on a concrete example from the stochastic control theory.
Keywords:

Interior-point methods , Quadratic programming , Stochastic programming , Programming in abstract spaces , Control problems

Language:
English
Published:
Communications in Combinatorics and Optimization, Volume:9 Issue: 2, Spring 2024
Pages:
353 to 387
https://www.magiran.com/p2678234