Scenario reduction for stochastic programs with conditional value-at-risk

DOI10.1007/s10107-018-1298-9zbMath1391.90436OpenAlexW2803693170MaRDI QIDQ1650782

Sebastián Arpón, Tito Homem-de-mello, Bernardo K. Pagnoncelli

Publication date: 13 July 2018

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10107-018-1298-9

Mathematics Subject Classification ID

Sensitivity, stability, parametric optimization (90C31) Stochastic programming (90C15) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (8)

Frameworks and results in distributionally robust optimization ⋮ Optimal non-anticipative scenarios for nonlinear hydro-thermal power systems ⋮ Effective Scenarios in Multistage Distributionally Robust Optimization with a Focus on Total Variation Distance ⋮ A New Scenario Reduction Method Based on Higher-Order Moments ⋮ Scenario-dominance to multi-stage stochastic lot-sizing and knapsack problems ⋮ Non-anticipative risk-averse analysis with effective scenarios applied to long-term hydrothermal scheduling ⋮ An Interior-Point Approach for Solving Risk-Averse PDE-Constrained Optimization Problems with Coherent Risk Measures ⋮ Risk and resilience-based optimal post-disruption restoration for critical infrastructures under uncertainty

Uses Software

• SUTIL
• NEOS

Cites Work

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