Risk minimization, regret minimization and progressive hedging algorithms

This paper begins with a study on the dual representations of risk and regret measures and their impact on modeling multistage decision making under uncertainty. A relationship between risk envelopes and regret envelopes is established by using the Lagrangian duality theory. Such a relationship open...

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Bibliographic Details
Main Authors: Sun, Jie, Yang, X., Yao, Q., Zhang, M.
Format: Journal Article
Language:English
Published: SPRINGER HEIDELBERG 2020
Subjects:
Online Access:http://purl.org/au-research/grants/arc/DP160102819
http://hdl.handle.net/20.500.11937/91434
Description
Summary:This paper begins with a study on the dual representations of risk and regret measures and their impact on modeling multistage decision making under uncertainty. A relationship between risk envelopes and regret envelopes is established by using the Lagrangian duality theory. Such a relationship opens a door to a decomposition scheme, called progressive hedging, for solving multistage risk minimization and regret minimization problems. In particular, the classical progressive hedging algorithm is modified in order to handle a new class of linkage constraints that arises from reformulations and other applications of risk and regret minimization problems. Numerical results are provided to show the efficiency of the progressive hedging algorithms.