Enhancing explainability of stochastic programming solutions via scenario and recourse reduction

DOI10.1007/S11081-023-09825-9MaRDI QIDQ6572717

Tushar Rathi, Qi Zhang, José M. Pinto, Rishabh Gupta

Publication date: 16 July 2024

Published in: Optimization and Engineering (Search for Journal in Brave)

zbMATH Keywords

stochastic programmingscenario reductionexplainabilityrecourse reduction

Mathematics Subject Classification ID

Stochastic programming (90C15)

Cites Work

• Generating Scenario Trees for Multistage Decision Problems
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• Introduction to Stochastic Programming
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• A New Scenario Reduction Method Based on Higher-Order Moments
• JuMP: A Modeling Language for Mathematical Optimization
• Random forests
• Problem-driven scenario clustering in stochastic optimization
• Optimization-Based Scenario Reduction for Data-Driven Two-Stage Stochastic Optimization

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