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Risk Minimization, Regret Minimization and Progressive Hedging Algorithms

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Listed:
  • Jie Sun
  • Xinmin Yang
  • Qiang Yao
  • Min Zhang

Abstract

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.

Suggested Citation

  • Jie Sun & Xinmin Yang & Qiang Yao & Min Zhang, 2017. "Risk Minimization, Regret Minimization and Progressive Hedging Algorithms," Papers 1705.00340, arXiv.org, revised Jun 2020.
    • Handle: RePEc:arx:papers:1705.00340
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    References listed on IDEAS

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    1. Jie Sun & Qiang Yao, 2017. "On coherency and other properties of MAXVAR," Papers 1703.10981, arXiv.org, revised Sep 2017.
    2. PAVLO A. Krokhmal, 2007. "Higher moment coherent risk measures," Quantitative Finance, Taylor & Francis Journals, vol. 7(4), pages 373-387.
    3. Karthik Natarajan & Dessislava Pachamanova & Melvyn Sim, 2009. "Constructing Risk Measures from Uncertainty Sets," Operations Research, INFORMS, vol. 57(5), pages 1129-1141, October.
    4. Aharon Ben‐Tal & Marc Teboulle, 2007. "An Old‐New Concept Of Convex Risk Measures: The Optimized Certainty Equivalent," Mathematical Finance, Wiley Blackwell, vol. 17(3), pages 449-476, July.
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