Decomposition algorithm for large-scale two-stage unit-commitment

DOI10.1007/s10479-015-2029-8zbMath1342.49046OpenAlexW1834552176MaRDI QIDQ271986

Wim van Ackooij, Jérôme Malick

Publication date: 20 April 2016

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-015-2029-8

zbMATH Keywords

nonsmooth optimizationconvex dualityprice decompositionbundle methodsdecomposition algorithmstochastic unit-commitmenttwo-stage integer programming

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Integer programming (90C10) Nonlinear programming (90C30) Stochastic programming (90C15) Numerical methods based on nonlinear programming (49M37) Decomposition methods (49M27)

Related Items

Inexact stabilized Benders' decomposition approaches with application to chance-constrained problems with finite support, Cut-sharing across trees and efficient sequential sampling for SDDP with uncertainty in the RHS, A comparison of four approaches from stochastic programming for large-scale unit-commitment, On conditional cuts for stochastic dual dynamic programming, Incremental Bundle Methods using Upper Models, Asynchronous level bundle methods, Adaptive Partition-Based Level Decomposition Methods for Solving Two-Stage Stochastic Programs with Fixed Recourse, Large-scale unit commitment under uncertainty: an updated literature survey, Fix-and-optimize procedures for solving the long-term unit commitment problem with pumped storages, Asynchronous Lagrangian scenario decomposition, Multiplier stabilization applied to two-stage stochastic programs, Regularized decomposition of large scale block-structured robust optimization problems, Parametric error bounds for convex approximations of two-stage mixed-integer recourse models with a random second-stage cost vector, Large-scale unit commitment under uncertainty

Uses Software

• astsa

Cites Work

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