A Model of Multistage Risk-Averse Stochastic Optimization and its Solution by Scenario-Based Decomposition Algorithms

Stochastic optimization models based on risk-averse measures are of essential importance in financial management and business operations. This paper studies new algorithms for a popular class of these models, namely, the mean-deviation models in multistage decision making under uncertainty. It is ar...

Full description

Bibliographic Details
Main Authors: Zhang, M., Hou, L., Sun, Jie, Yan, A.
Format: Journal Article
Language:English
Published: WORLD SCIENTIFIC PUBL CO PTE LTD 2020
Subjects:
Online Access:http://purl.org/au-research/grants/arc/DP160102819
http://hdl.handle.net/20.500.11937/91431
_version_ 1848765518749630464
author Zhang, M.
Hou, L.
Sun, Jie
Yan, A.
author_facet Zhang, M.
Hou, L.
Sun, Jie
Yan, A.
author_sort Zhang, M.
building Curtin Institutional Repository
collection Online Access
description Stochastic optimization models based on risk-averse measures are of essential importance in financial management and business operations. This paper studies new algorithms for a popular class of these models, namely, the mean-deviation models in multistage decision making under uncertainty. It is argued that these types of problems enjoy a scenario-decomposable structure, which could be utilized in an efficient progressive hedging procedure. In case that linkage constraints arise in reformulations of the original problem, a Lagrange progressive hedging algorithm could be utilized to solve the reformulated problem. Convergence results of the algorithms are obtained based on the recent development of the Lagrangian form of stochastic variational inequalities. Numerical results are provided to show the effectiveness of the proposed algorithms.
first_indexed 2025-11-14T11:36:32Z
format Journal Article
id curtin-20.500.11937-91431
institution Curtin University Malaysia
institution_category Local University
language English
last_indexed 2025-11-14T11:36:32Z
publishDate 2020
publisher WORLD SCIENTIFIC PUBL CO PTE LTD
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-914312024-04-11T03:40:15Z A Model of Multistage Risk-Averse Stochastic Optimization and its Solution by Scenario-Based Decomposition Algorithms Zhang, M. Hou, L. Sun, Jie Yan, A. Science & Technology Technology Operations Research & Management Science Progressive hedging algorithm risk-aversion stochastic optimization Stochastic optimization models based on risk-averse measures are of essential importance in financial management and business operations. This paper studies new algorithms for a popular class of these models, namely, the mean-deviation models in multistage decision making under uncertainty. It is argued that these types of problems enjoy a scenario-decomposable structure, which could be utilized in an efficient progressive hedging procedure. In case that linkage constraints arise in reformulations of the original problem, a Lagrange progressive hedging algorithm could be utilized to solve the reformulated problem. Convergence results of the algorithms are obtained based on the recent development of the Lagrangian form of stochastic variational inequalities. Numerical results are provided to show the effectiveness of the proposed algorithms. 2020 Journal Article http://hdl.handle.net/20.500.11937/91431 10.1142/S0217595920400047 English http://purl.org/au-research/grants/arc/DP160102819 WORLD SCIENTIFIC PUBL CO PTE LTD fulltext
spellingShingle Science & Technology
Technology
Operations Research & Management Science
Progressive hedging algorithm
risk-aversion
stochastic optimization
Zhang, M.
Hou, L.
Sun, Jie
Yan, A.
A Model of Multistage Risk-Averse Stochastic Optimization and its Solution by Scenario-Based Decomposition Algorithms
title A Model of Multistage Risk-Averse Stochastic Optimization and its Solution by Scenario-Based Decomposition Algorithms
title_full A Model of Multistage Risk-Averse Stochastic Optimization and its Solution by Scenario-Based Decomposition Algorithms
title_fullStr A Model of Multistage Risk-Averse Stochastic Optimization and its Solution by Scenario-Based Decomposition Algorithms
title_full_unstemmed A Model of Multistage Risk-Averse Stochastic Optimization and its Solution by Scenario-Based Decomposition Algorithms
title_short A Model of Multistage Risk-Averse Stochastic Optimization and its Solution by Scenario-Based Decomposition Algorithms
title_sort model of multistage risk-averse stochastic optimization and its solution by scenario-based decomposition algorithms
topic Science & Technology
Technology
Operations Research & Management Science
Progressive hedging algorithm
risk-aversion
stochastic optimization
url http://purl.org/au-research/grants/arc/DP160102819
http://hdl.handle.net/20.500.11937/91431