Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10107-003-0471-x
Title: A lagrangian dual method with self-concordant barriers for multi-stage stochastic convex programming
Authors: Zhao, G. 
Keywords: Interior point methods
Lagrangian dual
Multi-stage stochastic nonlinear programming
Polynomial-time complexity
Self-concordant barrier
Issue Date: Jan-2005
Citation: Zhao, G. (2005-01). A lagrangian dual method with self-concordant barriers for multi-stage stochastic convex programming. Mathematical Programming 102 (1) : 1-24. ScholarBank@NUS Repository. https://doi.org/10.1007/s10107-003-0471-x
Abstract: This paper presents an algorithm for solving multi-stage stochastic convex nonlinear programs. The algorithm is based on the Lagrangian dual method which relaxes the nonanticipativity constraints, and the barrier function method which enhances the smoothness of the dual objective function so that the Newton search directions can be used. The algorithm is shown to be of global convergence and of polynomial-time complexity.
Source Title: Mathematical Programming
URI: http://scholarbank.nus.edu.sg/handle/10635/102666
ISSN: 00255610
DOI: 10.1007/s10107-003-0471-x
Appears in Collections:Staff Publications

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