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math.OC2024★ 1 cited
A Quantile Neural Network Framework for Two-stage Stochastic Optimization
Antonio Alcántara, Carlos Ruiz, Calvin Tsay
Two-stage stochastic programming is a popular framework for optimization under uncertainty, where decision variables are split between first-stage decisions, and second-stage (or r…
math.OC2022
A Neural Network-Based Distributional Constraint Learning Methodology for Mixed-Integer Stochastic Optimization
Antonio Alcántara, Carlos Ruiz
The use of machine learning methods helps to improve decision making in different fields. In particular, the idea of bridging predictions (machine learning models) and prescription…
math.OC2022★ 17 cited
On data-driven chance constraint learning for mixed-integer optimization problems
Antonio Alcántara, Carlos Ruiz
When dealing with real-world optimization problems, decision-makers usually face high levels of uncertainty associated with partial information, unknown parameters, or complex rela…